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Keyword machine learning resume
Search Urlhttps://www.google.com/search?q=machine+learning+resume&oq=machine+learning+resume&num=30&hl=en&gl=US&sourceid=chrome&ie=UTF-8
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Result 1
TitleMachine Learning Resume: The 2022 Guide with 10+ Examples
Urlhttps://www.hiration.com/blog/machine-learning-resume/
DescriptionA machine learning resume is a resume that is tailored for Machine Learning professionals. Every aspiring Machine Learning Engineer is expected ...
DateOct 1, 2021
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Result 2
TitleMachine Learning Resume: Samples and Writing Guide - Zety
Urlhttps://zety.com/blog/machine-learning-resume-example
DescriptionFor an entry-level machine learning engineer resume, do the same thing with standard SWE achievements. The key? Scrape together your best coding moments that ...
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Result 3
TitleMachine Learning Resumes That Gets You interview Calls
Urlhttps://www.janbasktraining.com/blog/machine-learning-resume-sample/
DescriptionMachine Learning Resume Samples for Beginners & Professional · Strong knowledge of writing clean codes and debug large codebases · Knowledge of ...
DateDec 7, 2021
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Result 5
TitleMachine Learning Resume : Sample and Writing guide
Urlhttps://www.mygreatlearning.com/blog/machine-learning-resume/
DescriptionHow to write a Machine Learning resume step by step · Follow the right format · Clearly classify Education Section · Add relevant Skills clearly ...
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Result 6
TitleHow To Build a Strong Machine Learning Resume [+ Samples]
Urlhttps://www.springboard.com/blog/ai-machine-learning/machine-learning-resume/
DescriptionYour machine learning resume introduces you to potential employers, and an effective resume is a baseline requirement for moving forward in ...
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Result 7
TitleRezi Machine Learning Engineer Resume Template
Urlhttps://www.rezi.ai/resume-templates/machine-learning-engineer-resume-template
DescriptionMachine Learning Engineers are data scientists who apply statistical learning theories to build and improve systems in a wide range of industries, including but not limited to finance, medicine, telecommunications, and retail. For a Machine Learning Engineer to be positioned for success, he or she needs to have a technical background and expertise in mathematics, statistics, and computer science, in addition to a strong background in the field they're applying to. Based on our collection of example resumes, Machine Learning Engineers need to demonstrate technical expertise in the field of Machine Learning, strong problem-solving skills, and the ability to work independently. Most Machine Learning Engineers hold at least a Bachelor's Degree in Computer Science, Mathematics, or a related field
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H2Machine Learning Engineer Resume
Resume Certifications:
Where can I use this sample?
Get Started With 313 Ready-To-Use Free ATS Resume & Cover Letter Templates
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H2WithAnchorsMachine Learning Engineer Resume
Resume Certifications:
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Bodyhttps://www.googletagmanager.com/ns.html?id=GTM-W8VM27R" height="0" width="0" style="display:none;visibility:hidden"> Samples  •  Machine Learning Engineer ResumeMachine Learning Engineer Resume. Our classic resume template, trusted by over 100,000+ job seekers, is designed to get through ATS software and into the hands of real humans.Use This SampleDownload As Content DensityHighInterviewed atRating: 4.5 Engineered to get you hired at top companiesResume Certifications:. Where can I use this sample?Rezi Sample Library - First you'll need to create a free Rezi account, next you can navigate to the Sample Library page within your dashboard Get Started With 313 Ready-To-Use Free ATS Resume & Cover Letter Templates. Our sample resumes and cover letters are 100% focused on content - giving you inspiration on best practices.MarketingDirector of Content Marketing Resume. BusinessAssistant Policy Intern Resume. MarketingBrand Manager Resume Resume. ProgrammingTest Engineer Resume. BusinessOperations Manager Resume. FinanceActuary Resume. LegalLawyer Resume. MarketingMarketing Analyst Resume. See All SamplesReady to accelerate your job search?Create an account and get started.Click on the link below and get started using Rezi now with full access to all 300+ resume and cover letter templatesCreate Your Free Rezi Account Now
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Result 8
TitleMachine Learning Resume Samples | Velvet Jobs
Urlhttps://www.velvetjobs.com/resume/machine-learning-resume-sample
DescriptionMachine Learning Resume Samples and examples of curated bullet points for your resume to help you get an interview
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H1Machine Learning Resume Samples
H2The Guide To Resume Tailoring
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BodyMachine Learning Resume Samples 4.6 (44 votes) for Machine Learning Resume Samples The Guide To Resume Tailoring. Guide the recruiter to the conclusion that you are the best candidate for the machine learning job. It’s actually very simple. Tailor your resume by picking relevant responsibilities from the examples below and then add your accomplishments. This way, you can position yourself in the best way to get hired. Craft your perfect resume by picking job responsibilities written by professional recruiters. Pick from the thousands of curated job responsibilities used by the leading companies. Tailor your resume & cover letter with wording that best fits for each job you apply. Resume Builder. Create a Resume in Minutes with Professional Resume Templates CHOOSE THE BEST TEMPLATE - Choose from 15 Leading Templates. No need to think about design details. USE PRE-WRITTEN BULLET POINTS - Select from thousands of pre-written bullet points. 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Create a Resume in Minutes Create a Resume in Minutes DK D Kling Delphia Kling 78633 Hiram Corners Dallas TX +1 (555) 852 5479 78633 Hiram Corners Dallas TX Phone p +1 (555) 852 5479 Experience Experience 08/2014 – present Los Angeles, CA Software Engineer, Machine Learning Los Angeles, CA Software Engineer, Machine Learning 08/2014 – present Los Angeles, CA Software Engineer, Machine Learning 08/2014 – present Work with Data Scientists and Product Managers to frame a problem, both mathematically and within the business contextDeploy validated algorithms to our RTB system, and develop techniques for monitoring and visualizing performance of all deployed algorithmsKnowledge developing and debugging in C/C++ and JavaKnowledge of one or more open-source Machine Learning frameworkDevelop prototypes and validate the resultsExpert knowledge developing and debugging in C/C++ and JavaContribute to the production solutions’ development, testing and deployment 04/2011 – 05/2014 Phoenix, AZ Machine Learning Researcher Phoenix, AZ Machine Learning Researcher 04/2011 – 05/2014 Phoenix, AZ Machine Learning Researcher 04/2011 – 05/2014 Work closely with development teams to ensure accurate integration of machine learning models into firm platformsThis role will suit you if you thrive on working in a fast paced environment where your work has high impactDevelop the team’s capabilities in data science and machine-learning, and apply them to create new data-driven insightsCreate innovative, systematic investment signals and strategies based on a rigorous, peer-reviewed research processWork with every investment team in MBFI (Credit, Macro, Equities, RV, Securitized, Mid-horizon etc.) to introduce cutting-edge techniques and innovative data sources across the FundDesign, conduct, and report results from prototype or proof-of-concept research projects that focus on 1) new tools, methods, or algorithms, 2) new scientific domains or application areas, or 3) new data sets or sourcesDevelop new machine learning models to detect malicious activity on mobile devices 10/2006 – 10/2010 Detroit, MI Machine Learning Detroit, MI Machine Learning 10/2006 – 10/2010 Detroit, MI Machine Learning 10/2006 – 10/2010 Research & develop Machine Learning models for security problems, in the areas of Networking, Application & DataProvide SW specifications and production quality code on time to meet project mile stonesProvide SW specifications, production quality code and engage with algorithm proliferation activitiesResearch and develop deep learning algorithmsResearch and develop state of the art techniques in the field of computer vision, ML and DLWork with the system, physics, SW and application groupDevelop the next generation of automation tools for monitoring and measuring Ad Quality, with associated user interfaces Education Education Bachelor’s Degree in Computer Science Bachelor’s Degree in Computer Science Johnson & Wales University Bachelor’s Degree in Computer Science Skills Skills Excellent organizational and analytical skills Experience of developing data science capability Excellent written and oral communication skills Ability to read, understand, and communicate technical documentation Strong communication, presentation and business and technical writing skills Strong background in Python, SQL, and R. 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How to Write a Student Resume. 1 Data / Machine Learning Engineering Manager Resume Examples & Samples . Apply machine learning methods on large data sets Run small scale experiments with new algorithms and scale it up to 100B+ data points Work with other stakeholders and prioritize data/ML initiatives across the product Assume ownership over certain components and continuously work to improve them Focus on user impact and how to build a better product Be proactive and constantly pay attention to the scalability, performance and availability of our systems Be a crucial part of growing our team, by interviewing candidates and representing Spotify Help us tie connections to universities and research institutions, by leading collaborations and publishing research Stay up to date on current data engineering trends, in particular distributed systems and large scale machine learning Drive the recommendations technology agenda as a partner to product leaders Foster highly-dynamic cross-functional agile teams and leverage lightweight processes to deliver on new product objectives Lead the engineering of a continuous design, development, and testing lifecycle to bring features to market and measure their effectiveness 2 Senior Software Engineer Machine Learning Resume Examples & Samples . BS in Computer Science/Computer Engineering or comparable experience 5+ years of experience with an Object-Oriented programming language 2+ years of experience with Machine Learning, Statistical Models, and Natural Language Processing Experience with Python Solid understanding of Data Structures, Algorithms & Object-Oriented design concepts Team player with excellent communication skills Publications/Presentations in relevant communities (ICML, NIPS, CVPR, SIGIR, ACM Multimedia) is a strong plus Legal or financial domain expertise is a plus 3 Software Engineer, Search & Machine Learning Resume Examples & Samples . Monitor the quality of the graph and reduce duplicate entities across the site (and web) Increase the amount of metadata we have about each node and connectivity between entities Create APIs and services that allow third-parties to integrate with and utilize the entity graph Build/infer features that improve performance and other services (search, ads, feeds, etc.) 4 Machine Learning Software Student Resume Examples & Samples . Excellent Student at his 4th/5th semester, with at least 1.5 years before graduation Proficiency in SW development: good knowledge/experience with C/C++ Matlab, Python is a plus Ability to convert algorithms to efficient code Knowledge of Machine Learning is a plus Knowledge of Computer Architecture is a plus 5 Vertica Machine Learning Software Engineer Resume Examples & Samples . Design and implement state-of-the-art analytic techniques in our core database engine Design and implement APIs for integration with external algorithm packages Develop highly distributed algorithms based on Vertica APIs Gather and determine requirements for new features Develop and document intellectual property Proficient in C/C++ and R Machine learning and data mining techniques Research and/or working experience in distributed algorithms is highly desirable Productive in delivering production quality code and understand the balance between elegant and practical engineering solutions Knowledge of SQL, Systems or Database internals is a plus 6 Machine Learning Graduate Intern Resume Examples & Samples . Characterized deep learning techniques for upcoming Intel architecture, identify innovation opportunities and limitations Design new algorithms or adapt existing algorithms to leverage upcoming Intel architectures Develop Proof-of-concept implementations to prove out functionality and performance Tolerance of ambiguity Desire to advance the state of the art in the deep learning techniques The candidate must be working towards an MS degree in Electrical Engineering or Computer Engineering Minimum of 2 years experience in machine learning techniques including deep learning techniques, auto-encoders, neural networks, sparse coding Minimum of 2 years experience in computer vision and image processing algorithm development Minimum of 3 years experience in C, C++ and MATLAB or Python. OS experience with Unix/Linux Minimum 1 years of experience in machine learning algorithms internals for hardware/software acceleration Knowledge of standard development tools including revision control, debugging tools, compilers, shell scripting, etc Experience with computer system architecture Mobile platform development experience (Android/iOS) 7 Machine Learning Resume Examples & Samples . PhD in CS/EE (concentration in one of the following: information retrieval, machine learning, biometrics, data mining and predictive analytics) 5+ years professional experience developing product level algorithms and code Outstanding expertise and research experience on statistical machine learning, data mining, and information retrieval Excellent problem solving and data analysis skills Strong software design and development skills/experience Experience in Biometrics (Heart rate variability, calories, sleep analysis) is a plus Publication history in the fields of machine learning and data mining is a plus 8 Applied Machine Learning Eng Resume Examples & Samples . Develop high-performance machine learning systems for detecting abnormality, intrusion, fraud, masquerading, malware, etc Deliver end to end solution to analyze data that originates from users, services, or other automated systems Develop infrastructure as required to enable new experiences in enterprise intelligence by deriving meaning from vast array of enterprise data about users and their activity Actively engage other teams in Active Directory, Office 365 and Azure to identify problems and areas where data mining/machine learning/applied statistics can be used, and lead the development of solutions to these problems Act as an expert in the area of data mining/machine learning/statistics to serve the fast growing needs of Active Directory Experience with very large scale data processing/analysis (a.k.a. big data) Strong C++ and/or C# skills (C# preferred) and understanding of software design patterns Experience developing high-performance service-oriented solutions A Ph.D degree in Computer Science is highly desired. Candidates with a Ph.D in other quantifiable fields (e.g. Statistics, Mathematics) with applied practical experience and programming background are also desirable 9 Machine Learning Quant Resume Examples & Samples . Advanced degree in quantitative discipline (statistics, physics, computer science, engineering, etc) 3 + years of machine learning and data mining experience, preferably in financial industry Solid understanding of machine learning techniques including: Support Vector Machine/Regression, Hierarchical clustering, Distant based Clustering, and Decision trees Strong quantitative analysis and statistical modeling skills Track record of gathering, matching, and pre-processing large data sets from varied sources and of different characteristics Solid SQL (ideally MSSQL Server) programming skills Experience writing stored procedure preferred Professional experience in Matlab, VBA, or R. Nice to have c/c++ Familiarity with the Bloomberg Professional Service and Bloomberg data structure Strong Project and Time Management skills 10 Machine Learning & Health Informatics Expert Resume Examples & Samples . Expertise and hands-on experience in machine learning, including academic research in machine learning and health informatics Programming knowledge and experience - Java, python Expertise in NLP in the medical domain - an advantage Experience in scalable and parallel big data platforms and algorithms - an advantage Experience in developing application for mobile platforms - an advantage Doctorate Degree in Engineering Hebrew: Fluent 11 Software Engineer, Machine Learning Resume Examples & Samples . Large scale Machine Learning infrastructure that powers our Search ranking models Natural Language Processing to understand text content on Airbnb platform, including reviews, descriptions and interactions between users on our marketplace Identifying suspicious transactions and malicious users for Trust and Safety Determining the optimal pricing strategies to help our Hosts effectively manage their listings and achieve their revenue goals Modeling demand and supply situation in real time to optimize the overall market efficiency and give valuable insights to the Hosts Clustering of users and listings to enable more intelligent matching 12 Lead Machine Learning Software Engineer Resume Examples & Samples . Lead the full machine learning system implementation process: generating training data, model design, feature selection, system implementation, and evaluation Design and develop scalable recommendation platform that can be used by various systems/application Design and evaluate novel approaches for handling large scale data analyses and extract relevant information Apply data-mining, machine learning and/or graph analysis techniques for a variety of modeling and relevance problems involving users and their interests in various content types Collaborate with Engineers, QA, Product and Operations teams to architect and develop strategic and tactical solutions in the recommendation domain Provide technical leadership and mentoring to other team members.Participate in cutting edge research in machine learning applications BS/BA degree in Computer Science, Statistics, or related field, or equivalent work experience required Expert knowledge developing and debugging in Java on Unix and/or Linux 7+ years of full software development lifecycle experience Strong background in machine learning and data mining with a broad understanding of supervised and unsupervised learning methods (such as Regression, Decision Tree, Collaborative Filtering, PCA, Clustering, etc.) Strong mathematical skills with knowledge of statistical methods Extensive experience working with large data stores Understanding of content recommendation, personalization, and real-time data-mining Strong collaborative skills and the ability to work with team members from multiple roles to inform, influence, support, and execute our product decisions and launches Ability to mentor other team members and contribute to a collaborative team environment Passion for solving the world’s toughest problems, and the smarts to actually solve them Extensive experience building large-scale server applications is a plus Experience with Open source framework such as Hadoop, Hive, Spark, or Oryx is a plus 13 Machine Learning Internship Resume Examples & Samples . Work with the team in generating training data, model design, feature selection, system implementation, and evaluation Assist in designing and developing a scalable recommendation platform that can be used by various systems/application Apply machine learning and/or graph analysis techniques for a variety of modeling and relevance problems Participate in cutting edge research in machine learning applications Relevant knowledge of machine learning and data mining concepts with an understanding of supervised and unsupervised learning methods (such as Regression, Decision Tree, Collaborative Filtering, PCA, Clustering, etc.) Experience developing and debugging in Java on Unix and/or Linux Experience building large-scale server applications Experience with Open source framework such as Hadoop, Hive, Spark, or Oryx Experience working with large data stores 14 Software Engineer, Machine Learning Resume Examples & Samples . Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models MS degree in Computer Science or related quantitative field with 5 years of relevant experience or Ph.D degree in Computer Science or related quantitative field Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, large-scale data mining or artificial intelligence Experience with Hadoop/Hbase/Pig or Mapreduce/Sawzall/Bigtable Expert knowledge developing and debugging in C/C++ and Java Experience with scripting languages such as Perl, Python, PHP, and shell scripts Experience with filesystems, server architectures, and distributed systems a plus 15 Master Thesis Speech Recognition & Machine Learning Resume Examples & Samples . M.Sc. student, preferably in computer science, electrical engineering, engineering physics or similar Courses within Signal Processing, Video & Speech processing, Machine learning is an advantage Further proficiency in C and Matlab is required 16 Senior Machine Learning Resume Examples & Samples . 3+ years in Natural language processing or Machine learning 1+ years of OOD experience Able to apply NLP theory to practical problems Able to lead projects from an idea to production deployment 17 Watson Software Developer Text Analytics & Machine Learning Resume Examples & Samples . Experience in Java or C++ Proven foundation in core CS competencies such as data structures, algorithms and software architecture Formal knowledge with natural language processing, text mining and machine learning algorithm implementation Preferred Experience: Knowledgeable in development or use of ontologies such as Unified Medical Language System (UMLS), Financial Industry Business Ontology (FIBO) or Web Ontology Language (OWL), or familiarity with Resource Description Framework (RDF) Preferred Experience: knowledge with machine learning technologies such as SPSS or Apache Mahout Proven communication skills and drive to get things done Demonstrated foundation in scripting fundamentals such as Unix command-line, regular expressions, file manipulation, etc Demonstrated foundation in core CS competencies such as data structures, algorithms and software architecture Experience working in a Linux development environment 18 Machine Learning Resume Examples & Samples . Masters studies in algorithms and/or machine learning Comfortable working in Unix environments · A general interest in computer and network security Self-driven and well structured Fluent in written and spoken English 19 Data Engineer, AI / Machine Learning Resume Examples & Samples . Work on a wide variety of problems in search/information retrieval, natural language processing, unsupervised and supervised learning problems, crowd sourcing, and data enrichment Using quantitative research, you will help identify, design and implement machine learning models that help enrich Autodesk’s data improving our evidence based decision making Working with a team of developers you will be integral to building full stack internal applications that are consumed throughout Autodesk Have the opportunity to become expert in new technology and help the team remain current in its practice. We currently use Spark, Hive, Python, R and various NoSQL technologies with the goal of using the most appropriate tool for the job. It is most important that you are a strong programmer with a growth mindset who can help round out the expertise in the team The team is motivated by learning and we want a creative mind with who we can work together to find solutions to difficult problems 20 Automated Driving Engineer Machine Learning Resume Examples & Samples . Ph.D. in Electrical Engineering, Computer Science, or similar fields, with five years of equivalent experience Experience with computer vision, machine learning, DNNs, and Numerical Optimization Experience with algorithms such as motion control, image processing, simultaneous localization and mapping, geospatial location, rendering 3D data, computer graphics, etc Knowledge of 3D coordinate frames and transformations, vector mathematics, matrix algebra, probabilistic inference and modeling, etc Experience in multiple computer hardware, operating systems and tools, e.g., embedded microcontrollers, GPUs; Windows, UNIX, Linux; git, Make, subversion glibc, gcc, bash, etc Proficiency in writing optimized code in multiple contemporary computer programming languages, e.g., C/C++, PERL, Python, Java, OpenGL, MATLAB/Stateflow/Simulink, etc Experience with sensing systems such as cameras, radar, lidar, GPS, IMUs, etc Experience with system requirements, testing, validation, software release Experience with the CUDA platform Expert experience in designing and building state of the art feature detectors and trackers 21 Machine Learning Researcher Resume Examples & Samples . Semantic text mining or natural language processing Spark, Hadoop or other MapReduce implementation experience Experience with database technologies such as SQL or NoSQL Experience developing component using IBM Watson services and APIs Delivered models used for Recommender Systems Experience with Cloud Based Data Management such as Cloudant 22 Machine Learning & Artificial Intelligence Engineer Resume Examples & Samples . To design and build an autonomous system to carry out the below activities Programming knowledge; specifically techniques for mining large amounts of unstructured data, text analytics and natural language processing Knowledge of machine learning and practical applications of artificial intelligence Experience in piecing together disparate sources of information to create actionable intelligence Ability to rapidly summarise large amounts of information and give presentations Knowledge of data warehousing and cloud services, e.g. AWS Ability to work within a team split across countries and manage own workload without supervision Ability to travel occasionally as required LI-MM2 23 Machine Learning Research Engineer Resume Examples & Samples . PhD in Computer Engineering, EE or similar field Smart and versatile New Grads with a big appetite for making milestone changes in technology Being a tinkerer and experimenter with ideas that contribute towards real change Masters in Computer Science or related technical field. Computer Science fundamentals: data structures and algorithms. Desired proficiency in one of these programming languages ­ Java, Python, C, C++, C# Strong analytical skills including the ability to define problems, collect data, establish facts and draw valid conclusions Excellent collaboration and time management skills Ability to communicate and promote your ideas Skilled in translating research findings into realizable solutions New or recent Ph.D. in Computer Science or related technical field prior machine learning experience Experience with Agile software development process Understanding of the mobile device landscape Experience in Android or IoS software development 24 Master Thesis on Analytics & Machine Learning for IoT Resume Examples & Samples . Bachelor degree in computer science, or engineering Programming skills in Java, Python, Matlab, R Data mining, machine learning knowledge Signal processing, pattern recognition, nature language processing Innovative and creative thinking Passionate to win English written and spoken 25 Machine Learning for Autonomous Vehicles Research Engineer Resume Examples & Samples . Master’s Degree in Computer Science, Electrical Engineering, Robotics or Statistics 1+ year of experience developing machine learning models such as using deep learning methods for classification and regression PhD in Computer Science, Electrical Engineering, Robotics, Statistics, or related field Hands on experience with at least one of the following tools: Caffe, TensorFlow, Theano, or a similar deep learning toolkit Experience with Python, Java, C/C++ or other related languages Experience with Matlab/Simulink Experience with image processing and computer vision Experience in developing control and optimization algorithms Comfortable working in an environment where problems are not always well-defined 26 Machine Learning R&D Engineer Resume Examples & Samples . Hadoop or other MapReduce implementation experience Ability to build and interpret probabilistic models of complex, high-dimensional systems Solid programming experience utilizing Java, C, C++ or Python Delivered models in high-stakes information retrieval and statistical analysis, e.g. Bioinformatics, Fraud Detection, Education MS in Computer Science, Artificial Intelligence, Machine Learning, or related technical field Delivered models in high-stakes information retrieval and statistical analysis, e.g. Bioinformatics, Fraud 27 Technical Sourcer, Machine Learning Resume Examples & Samples . Work closely with Recruiters and hiring managers to deeply understand technical requirements of the role, the function and how it fits into the organization Team with Coordinators and Recruiters to manage an efficient model of operation Strategize different ways to build talent pipelines and execute on tactical research, referral generation, events and sourcing campaigns Find, engage and activate passive candidates through the use of Boolean, LinkedIn and alternative search techniques Screen resumes and interview candidates to determine fit Regularly track pipeline activity to share with internal stakeholders Recommend and drive improvements that impact local pipeline areas Embody Facebook’s culture: Be Bold, Move Fast and Focus on Impact 28 Software Engineering Lead-analytics & Machine Learning Resume Examples & Samples . Determines specifications, then plans, designs, and develops the most complex and business critical software solutions, utilizing appropriate software engineering processes-either individually or in concert with project team Designs and produces detailed technical architecture guidelines and standards for the use of relevant core technologies and protocols Researches and maintains knowledge in emerging technologies and possible application to the business Assists in troubleshooting the most difficult and mission-critical technical problems Acts as an internal consultant, advocate, mentor and change agent Typically possesses 5 to 7 years of relevant work experience Experience in the following technologies 29 Software Engineer Machine Learning Resume Examples & Samples . Attractive collective health care insurance package with considerable reduction rates Solid Pension Plan of which 70% of the premiums is paid by Elsevier Profit share or bonus plan subject to the company annual results 30 Senior Machine Learning Expert Resume Examples & Samples . University graduate (Master of PhD level) computer science, Artificial Intelligence, computational linguistics or an associated area Minimum of 5 years of experience in Machine Learning or a similar role Solid software engineering skills and experience including coding, testing, troubleshooting and deployment. With experience using key languages like JVM-based languages (Java, Scala, Clojure), C++ and Python Large scale data processing experience using Spark or Hadoop/MapReduce Solid Experience in machine learning including supervised or unsupervised learning techniques and algorithms (e.g. k-NN, SVM, RVM, Naïve Bayes, Decision trees, etc.) Familiarity with cloud computing (AWS) Experience with git or a similarly distributed revision control system You think a working proof-of-concept is the best way to make a point Relevant certificates (Spark, Hadoop / Cloudera or CBIP) is a plus Experience working with a variety of stakeholders at the mid and senior management level and ability to coach junior members Solid Pension Plan, with a choice between a collective pension plan an individual pension plan You can participate in the convertible personnel bond scheme Flexible working arrangements Reductions to several personal insurance packages due to our collective agreements Additional benefits, such as memberships to Elsevier’s magazines, discount on books and in-house sport facilities Various social responsibility programs, channeling knowledge and strengths to help communities around the world improve education, science, health care and protect the environment 31 Automated Driving Research Engineer Vision & Machine Learning Resume Examples & Samples . Design effective and efficient feature detection and tracking systems Design, train and evaluate various machine learning systems for use in object detection and semantic scene understanding Develop new ways to use image features or tracking to improve the mapping and localization algorithms Evaluate and compare deep learning algorithms for specific applications and related tasks to improve performance, training, and suitability for embedded applications Maintain close contact to the scientific and industrial community in machine learning and perform scouting and assessment of new approaches Present results for internal management and at external venues such as conferences Ability to carry out independent research and lead projects Ph.D. in Engineering, Natural Sciences or related technical fields 1+ years of experience in multiple contemporary computer programming languages, e.g., C/C++, PERL, Python, Java, OpenGL, MATLAB/Stateflow/Simulink 3 or more months hands-on experience in Deep Learning or Machine Learning Computer vision, machine learning, DNNs, and Numerical Optimization experience Algorithms such as motion control, image processing, simultaneous localization and mapping, geospatial location, rendering 3D data, computer graphics experience Knowledge of 3D co-ordinate frames and transformations, vector mathematics, matrix algebra, probabilistic inference and modeling, etc Familiarity with existing deep learning libraries (e.g. Torch, Theano, Caffe, PyBrain, Neon ) Sensing systems such as cameras, radar, lidar, GPS, IMUs experience Possess strong oral and written language skills 32 Lead Machine Learning Researcher Resume Examples & Samples . Lead the projects and provide technical execution to design of machine learning algorithms/solutions to solve industrial problems at GE Determine methodologies needed; apply such methodologies (e.g. graphical models, neural nets, CART, Bayesian methods, etc.) on monitoring, classification, prediction, controls, bioinformatics, computer vision and related research domains Define data needs, evaluate data quality, perform and critique appropriate statistical analyses using software such as R, Python, SAS, MATLAB, and/or Splus. Explore, determine & develop technical approaches to be used and apply them on major challenges Establish synergies with other GE research labs and software engineering team to drive Industrial Internet vision utilizing big data, domain knowledge and modern machine learning and artificial intelligence techniques Interface closely with GE Business counterparts to understand/define requirements, domain knowledge/models, and data needs Effectively communicate technical analysis and results Support proposals to respond to internal and external funding opportunities Doctorate degree in Computer Science, Mathematics, Applied Statistics, Operations Research or in Engineering Foundation in theories underlying machine learning techniques At least 3 years of experience in applying theoretical or experiential knowledge on machine learning & artificial intelligence to solve real world problems Experience in developing machine learning packages with modern programming languages Legal authorization to work in the U.S. is required. We will not sponsor individuals at the Masters or BS level for employment visas, now or in the future, for this job opening Must be willing to work out of an office located in San Ramon, CA You must submit your application for employment on the careers page at www.gecareers.com to be considered Experience with designing and prototyping algorithms on industrial data Strong knowledge in text analytics area Experience in applying machine learning to industrial problems Programming skills/ experience in high level languages like Java, .NET, Hadoop and Cloud computing Knowledgeable with relational databases & SQL concepts. Compute platforms like Matlab Interest/Experience in large data sets, cloud based architectures and deployment frameworks for machine learning algorithms. Open source efforts in machine learning Strong analytical skills, with demonstrated reputation including publications / development / deployment experience Ability to take initiative and deliver tangible results under deadlines Ability to work under uncertainty Flexibility of working across all functions/levels as part of a team 33 Software Architect Machine Learning Resume Examples & Samples . Evolve the current architecture to excel in machine learning, AI and Data analytics approaches Gathering business requirements with clients in visualization sessions to plan, design and implement mobile applications, web applications, database designs, network architecture and hybrid solutions Keep the solution on the cutting edge of IT security to protect our data Work together with internal stakeholders to define new services and plan development sprints accordingly Create and execute practical research to understand the voice of the customer in solving problems Experienced in using- Node JS, AngularJS, MySQL, SQL, Azure, AWS, NoSQL, MapReduce, Hadoop, Power BI and Azure Data factory and Bootstrap Strong understanding of Microsoft technology stack and the ability to match them to client processes to meet their business needs Master in Computer Science Highly motivated employee with the ability to work on multiple tasks with a high degree of flexibility in a fast-paced environment Proven ability to provide oversight for multiple development projects simultaneously, and resolve high level execution issues across company functions Self-starter who can identify opportunities based on other industries and analogous businesses 34 Machine Learning SDE Resume Examples & Samples . Relevant software design and development in C++, C# or Java At least a Bachelor’s Degree in Computer Science, Computer Engineering, or equivalent Strong background in machine learning with application in: medical image analysis or computer vision Excellent production-grade programming skills Strong background in math and statistics Outstanding technical problem solving and debugging skills Effective communication skills and an entrepreneurial spirit to succeed in a fast-paced team Experience with OpenCV libraries, ITK/VTK, CUDA, deep learning Experience with V1 products or start-up environment 35 PhD & Postdoctoral Recruiter Machine Learning Resume Examples & Samples . Manage the full-cycle recruiting process for PhD new graduates, interns and postdoctoral researchers with expertise in Machine Learning Act as a resource to PhD interns throughout their internship including on-boarding, performance evaluation, and conversion process Innovate on ways to build a talent pipeline from top PhD programs in machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence BA/BS degree with 3+ years of experience recruiting engineering candidates Passionate about Facebook and able to speak to our technology/industry Broad knowledge of programming languages, web technologies, software development process and emerging technologies Experience with managing nuanced programs Ability to travel during peak recruiting cycles 36 Machine Learning Researcher Resume Examples & Samples . PhD or PhD candidate in machine learning, computer science, statistics, or a related field Superb analytical and quantitative skills, along with a healthy streak of creativity Demonstrated ability to conduct independent research utilizing large data sets Passion for seeing research through from initial conception to eventual application Curiosity about financial markets Strong scientific programming in Python, R or Matlab Empirical, detail-oriented mindset Sense of ownership of his/her work, working well both independently and within a small collaborative team 37 Machine Learning Resume Examples & Samples . Professional work experience as a Data Scientist on projects with recent hands-on experience working with data mining tools like SAS, SPSS, R, Python or S+ is required Experience working on distributed computing platforms such as those based on Apache Hadoop and cloud services like Amazon’s EC2 makes it easier and cost-effective Understanding of probability, statistics, algorithm development and the common libraries/packages/APIs used in this field (e.g. Caffe, scikit-learn, Theano, Spark MLlib, H2O, TensorFlow etc) Experience advising customers on architectures meeting industry standards 38 Senior Engineer, Machine Learning Resume Examples & Samples . Build and implement scalable, enterprise grade machine learning applications to provide data driven insights to end users including sales reps, sales operations, pricing, legal finance, and executive managers Design and develop architecture for building and deploying scalable cloud based predictive and prescriptive intelligence solutions such as recommender systems Collaborate with data scientists, software engineers, product managers and customers to identify best machine learning solutions to optimize the revenue funnel 39 Machine Learning Expert Resume Examples & Samples . Understand the business problem, identify the key challenges, formulate the machine learning problem and prototype solutions Debug and correct your data assumption through AB testing Document the technical details of your work Collaborate and brainstorm with other team members Assess the methodological and functional pros and cons of implementing third-party products versus building an in-house system when facing a business problem Collaborate extensively with stakeholders, program management, and software development team members to ensure that solutions meet business needs, permit valid inferences, and have functional feasibility Passion about solving real world machine learning problems Strong publication record at top machine learning conferences, (ICML, KDD, WWW, RecSys, ACL, ICDM) PhD in one of the machine learning related fields: deep learning, graphical modeling, learning to rank, data mining and web mining. Postdoctoral work highly desirable Strong programming skills, at least being efficient with one low level language, c++/java, and one of scripting languages python/R/scalar Experience with Torch, Tensorflow Experiences with distributed computing (Hadoop/Spark) 5+ years’ experience of working with real data (data cleaning, data visualization and modeling) (can include time in academia/research) 40 Machine Learning & Artificial Intelligence Leader Resume Examples & Samples . Engage business leaders to discuss the business benefits that ML and AI can provide Identify opportunities to leverage ML and AI technology to drive tangible business value Create broad business insight for our enterprise using ML and AI tools Define the Machine Learning and Artificial Intelligence technology strategy Lead the direction for technology investments in the ML and AI areas Create and manage use cases to apply ML and AI concepts Evangelize ML and AI throughout the enterprise and in the market Create a roadmap to continually enhance our ML and AI capabilities Advanced degree in Data Science, Computer Science, Statistics, Applied Mathematics or related quantitative field Demonstrated expertise in Machine Learning (ML) and Artificial Intelligence (AI) concepts Deep knowledge of ML, AI, Big Data and Analytics platforms and tools Track record of success applying ML and AI concepts to business opportunities and/or problems Proven ability to explain the value of ML and AI to business leaders 10 + years of experience in statistical analysis and predictive analytics Executive with a minimum of 15 years of demonstrated progressive career accomplishments Proven experience driving large-scale technology initiatives across complex, global organizations Demonstrated executive leadership qualities, including presentation, influencing and negotiation Experience in strategic planning Track record of success leveraging relationships and leadership skills to get things done through matrixed teams Healthcare industry Publications and conference presentations in the Data Science space IBM Watson SAS Advanced Analytics and modeling Hadoop Python DSSTNE TensorFlow Azure 41 Machine Learning Senior Researcher Resume Examples & Samples . Independently design and undertake new research as well as partner in a team environment across organizations Develop topic descriptions for creative and innovative approaches to solving challenges Provide leadership & organization to other team members Design and implement secure, scalable, and fault-tolerant solutions across a distributed architecture, with the objective of researching and developing machine learning approaches, especially deep learning, applicable across multiple domains Track record of relevant publications in peer-reviewed conferences and journals Knowledge of state-of-the-art methods coupled with the creativity and intelligence to advance beyond them Leadership abilities necessary to lead projects Strong data analysis skills using R or a comparable platform, and one programming language, e.g. Python, Perl, C/C++, Java The ability to obtain and maintain a TS/SCI security clearance Advanced degree in machine learning (Ph.D highly desired) or a related discipline, such as artificial intelligence. 8 years of overall experience is preferred PhD in Machine Learning or Artificial Intelligence with publication track record Familiarity with existing deep learning libraries (e.g., CUDA, Caffe, Theano, Torch, Nvidia Digits) Prior experience with a few of the following models: Logistic Regression, Linear Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Latent Dirichlet Allocation Experience in GPU development (including GPGPU iOS) 42 Machine Learning & Data Analytics Research Researcher Resume Examples & Samples . Work within a distributed team of scientists and engineers at ATL, other Lockheed Martin facilities, outside companies, and universities to perform research in machine learning, human systems integration, human performance augmentation, and human-system teaming, as well as perform modeling, simulation, and analysis Research will focus on generating approaches that can be used to enhance Lockheed Martin’s goal of enabling human-system teaming and to making leaps ahead in human-system effectiveness R&D could take place in the areas of machine learning, human-systems integration, human-robot interaction, performance monitoring, or adaptive training A minimum of 1 year research and development experience in a relevant area, including co-op or internships Teamwork and research collaboration skills Demonstrated successful research project leadership Experience in research studies surrounding human effectiveness Ability to travel occasionally 43 Machine Learning & Data Analytics Researcher Resume Examples & Samples . Typical customers include DARPA, IARPA, ONR, AFRL, ARL, commercial companies, Lockheed Martin business units, and Advanced Technology Labs proper (via internally funded basic and applied research programs) Applicants are expected to have ideas for research and have a desire to see these research concepts funded Applicants selected will be subject to a government security investigation Degree in Computer Science, Cognitive Science, Artificial Intelligence, Cognitive Psychology, Information Science, Neuroscience, Psychology, Neurology, or related discipline with a focus on design, development, application, and evaluation of machine learning and advanced data collection, statistics and analysis methods. These methods will be applied to advance human-machine interaction technologies to attain high levels of human-system performance Experience in defining research objectives, preparing and presenting research plans and results to management and customers, developing research proposals, and planning, implementing, and tracking of R&D projects Ability to support proposals to win DoD-funded contracts, team with university researchers in the human factors and human-system integration domains, and collaborate with small and medium enterprise companies Must have the ability to obtain a U.S. Secret Security clearance that requires U.S. citizenship. Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information Knowledge of current state of the art in machine learning techniques, data analysis, statistics, experimental design, and familiarity with applying these methods to the human sciences Verbal and written skills and ability to present complex technical issues M.S. or equivalent research experience in one of the above technical disciplines; a background in signals processing is a plus Experience in transitioning technology from the research environment to users 44 Machine Learning System & Performance Architect Graduate Intern Resume Examples & Samples . Background in hardware architecture (pipelining, memory hierarchies, DRAM characteristics, power and area estimates, etc.) Experience developing optimized and parallelized machine learning kernels or applications for at least one hardware target, such as multicore Intel CPUs/SSE/AVX, GPUs, or custom accelerators Ph.D., or experience in a research environment such as a national lab, or 4+ years industry experience 45 Applied Machine Learning Resume Examples & Samples . Directly assist and support Government leadership in all technical aspects of managing multiple research and development (R&D) projects and contracts, to include providing expert technical advice and insights about relevant technologies Analyze technical data deliverables and publications from development contractors to assess the significance of their results and identify technical issues Provide coordination and technical oversight of testing and evaluation of Program efforts / deliverables by development contractors, to include analysis of data and results Provide independent review and summary of current technical literature, including surveys and summaries of relevant Government, academic, and contracted research Provide technical and programmatic support for emerging concepts, studies, projects, technologies and other work in related areas Draft summary briefings and reports and support periodic reviews and impromptu reporting requirements Analyze and resolve financial and programmatic issues in collaboration with a program analyst In addition to the level of effort support to the program, support may be required for seedling projects and other program related activities College Park, MD Bachelors Degree 14 years of work experience At least 5 years of experience in applied machine learning At least 3 years of experience with computer vision and image processing At least 3 years of experience with electro-optical and multi-spectral data At least 1 year of experience with synthetic aperture radar At least 1 year of experience with satellites Active TS SCI w/Poly clearance PhD with 9 years of experience At least 5 years of experience working with satellites At least 5 years of experience working with synthetic aperture radar Experience with transition partners Experience with the Intelligence Community Experience with test and evaluation teams Experience working on advance R&D programs 46 Machine Learning Researcher Resume Examples & Samples . Conduct research in the field of deep learning applied to text analysis Efficiently implement algorithms and run experiments on real data Integrate algorithms as software components in a complex development environment PhD in computer science. Outstanding MSc graduates may also apply Strong background in machine learning and deep learning Hands on experience in writing code Innovative thinking, creative and capable of thinking Experience in Java and/or Python Excellent academic track record in machine learning and/or natural language processing research Authorized to work in Israel or hold an applicable work permit required by the Israeli law Excellent programming and engineering skills Good research and self-learning skills Experience in scalable and parallel big data platforms and algorithms 47 Principal Engineer Machine Learning Resume Examples & Samples . Together with domain expert, identify opportunities to apply Machine Learning/ Artificial Intelligence technologies for network performance analysis and optimization. To gain insights from data about what’s happening, why happening and what actions to take As a lead investigator, propose and direct technology projects in solution architecture and key algorithm design and verification Achieve technology breakthrough and innovation by combining technology insights and business opportunities. To monitor the progress and industrial trends; propose technology strategy and roadmap to support the decision making of executives Organize and participate in global conference/events to promote Huawei technology visibility and branding 48 Software Engineer, Machine Learning Resume Examples & Samples . Work with Data Scientists and Product Managers to frame a problem, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Construct and fit statistical, machine learning, or optimization models Write production modeling code; collaborate with Software Engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings; facilitate launch decisions M.S. or Ph.D. in Statistics, Operations Research, Mathematics, Computer Science, or other quantitative field 2+ years professional or research experience Passion for solving unstructured and non-standard mathematical problems End-to-end experience with data, including querying, aggregation, analysis, and visualization Proficiency with Python, or another interpreted programming language like R or Matlab Willingness to collaborate and communicate with others to solve a problem 49 Machine Learning Researcher Resume Examples & Samples . As a part of the Research Innovation Team with the DSCoE, you will drive the development of solutions for complex data science challenges across the organization. This includes working with diverse data sets and across scientific domains. Examples range from digital agriculture and synthesizing large, spatial and spatial-temporal datasets to the analysis of genomic data Design, conduct, and report results from prototype or proof-of-concept research projects that focus on 1) new tools, methods, or algorithms, 2) new scientific domains or application areas, or 3) new data sets or sources Partner with diverse research groups to understand their research problems, models, product, and data needs and provide advice, coordination, and mentorship Communicate results to stakeholders in various parts of the organization, including other research teams, business groups, and leadership Write beautiful, robust, and well-documented research code Ph.D. in statistics, computer science, machine learning, or a related field Experience with using R or python for research Experience developing and applying machine learning methodology for solving complex applied problems Experience with developing and applying deep learning algorithms Experience and interest in interdisciplinary research Excitement to learn new topics, explore new datasets, and use new tools Drive to solve problems, meet deadlines, and build whatever is necessary along the way Strong communication and collaboration skills 50 Cloud Applications Developer for Machine Learning Incubation Team-singapore Resume Examples & Samples . Performing quality assurance tasks Immerse yourself quickly into new topics, terminology and development tasks Degree in Computer Science or related field Track record of developing novel cloud applications and/or systems Proficiency in handling of huge data sets and building scalable solutions Experience with cloud solutions such as Cloud Foundry, OpenStack, AWS, Terraform, etc Experience in end-to-end development stack with programing languages such as Java, Python, C++; Databases such as MongoDB, Cassandra, PostgreSQL, Redis; Libraries / Tools such as Mesosphere, Spark, Chronos, Kafka, Jenkins, Sonar, JMeter; Frontend development skills such as HTML5, JavaScript, Bootstrap, AngularJS etc Ability to visualize work results in a clear and compelling way Strong desire to overcome obstacles and make your work benefit SAP's customers Excellent written and communication skills in English language 51 Developer for Machine Learning Resume Examples & Samples . Apply relevant research domains with the ability to synthesize a wide range of requirements for analytical database management system Modeling data mining and recommendation solutions Designing software architecture to best exploit modern parallel processing Work closely with architects, UX designers, web developers, and quality specialists to design and implement cutting edge products for database management system Work with Agile Software Development methodology Ensure deliverables meet QA standards, specs, and client expectations Work closely with a distributed team over several international locations Knowledge on machine learning and deep learning research Extensive experience on database management systems Knowledge developing and debugging in C++ Lots of experience with Linux/UNIX systems and the best practices for deploying applications to those stacks Practical experience in technical writing and creating documentation would be considered an advantage Willingness to learn and flexibility to switch to new subject matters quickly Excellent team player, self-motivated, with strong communication skills MS/ PHD degree in Computer Science or related field Proficiency in English language; daily communication will be done in English 52 Developer for Machine Learning Platform Resume Examples & Samples . Build platform services and tools to support efficient creation and delivery of machine learning services Work in a diverse team applying Scrum and agile development Collaborate with remote location teams Master’s degree in computer science, engineering or equivalent education Proficiency in one or more of Java, Python, Node.js, Scala, Go, or Rust Experience with cloud-based development using Cloud Foundry, Docker, AWS, Azure or other container/PaaS environments Extensive experience in REST API implementation Exposure to microservice architectures, development and operations Hands-on experience on continuous integration and build tools like Jenkins, Travis CI Experience with Test-Driven Development (TDD) Agile/scrum experience 3+ years of experience in relevant roles 53 Business Developer for Machine Learning Incubations Resume Examples & Samples . Engage with customers to validate the fit for co-innovation projects for existing machine learning use cases Engage with customers requesting co-innovation projects on machine learning to derive tangible new use cases Investigate and shape market and customer perspectives for the given use case with the aim to identify the most promising Work with machine learning and industry experts to validate feasibility and viability of potential solutions Accompany, monitor and supervise product development and release processes Drive the commercialization and market entry through reference customers Master’s degree in business administration, engineering or equivalent education Proven track record in business development and Go-To-Market of new products Ability to present to senior management and to executive level Excellent English and German language skills At least 3 years of experience in relevant roles 54 Developer for Machine Learning Applications Resume Examples & Samples . Work through user given problems from beginning to end:translating research insight into adequate user experience & software concepts for SAP’s customers Degree in computer science or related field; Master’s degree preferred Ability to prototype what you design & conventionalize Excellent communicator of design & concept work and your rationale behind proposals to internal stakeholders and customers Intuition and understanding of Design Thinking methodologies and design principles Strong visualization and presentation skills Knowledge of full stack software development with the respective technologies used at SAP (Java, JavaScript, ABAP, Python & SQL) Self Starter and team player who can deeply collaborate with team members and stakeholders Excellent English and German communication and language skills 55 Senior Engineer Machine Learning Resume Examples & Samples . Ad server algorithm development for performance behavioral targeting & speed Enable large video advertisers to run efficient marketing campaigns that exceed aggressive ROI goals with precision and efficiency Implement ad targeting models that use advanced statistical and machine learning techniques Analyze, design and implement targeted relevance algorithms Develop and implement algorithms that work with large scale data to forecast and optimize return on online advertising Collaborate with product management and engineering to explore tradeoffs of performance and accuracy with alternate statistical approaches MS/PhD in Computer Science, Statistics or related fields is required 7+ years of hands on experience in machine learning using large & variant datasets Must have strong hands on experience in Python Proven track record in independently developing complex machine learning based systems, utilizing multiple machine learning frameworks and techniques for optimal accuracy and performance Must have solid understanding of statistical modeling/machine learning/ data mining/ recommender systems concepts on larger data Demonstrated ability to deal with very large datasets Strong knowledge of data structure, modeling, replication and distributed data/object relational database mapping Strong analytical quantitative and problem solving ability Experience with architecting, building and deploying reliable algorith-ms-based ad optimization systems that work at scale Experience with Python, relational databases (MySQL preferred) and Unix/Linux experience are required Experience in Hadoop, Hive , Map/Reduce & programming streaming is desirable Hands on experience working with Java or C++ is preferred 56 Senior Research Engineer, Machine Learning Resume Examples & Samples . Lead development of proprietary machine learning technologies that drive adaptive, personalized recommendation services, predictive analytics capabilities, data extraction scripts, data visualizations and other software required to support R&D Work closely with scientists with expertise in diverse fields, and other partners, to transfer proof of concept systems into production at scale Collaborate with data scientists to deliver valuable analytics for product and marketing teams, providing insights about customer behavior and product performance metrics Identify and promote the use of new technologies, toolkits and frameworks, areas of inquiry, ways of working, methods and approaches in Computer Science, Software and Research Engineering that helps the lab continue to push the boundaries of innovation Serve as outstanding model of individual and group performance. Support mentoring of less senior members of the team when needed B.Sc. in Computer Science, Engineering, Applied Statistics or a related quantitative field(s). Master’s or Ph.D. degree a plus Experience with machine learning and data mining in practice Experience with using machine learning frameworks and toolkits such as Spark, Weka, Mahout or Hadoop Familiarity with natural language processing and information search and retrieval tools like Solr, Lucene, NLTK, OpenNLP Strong engineering background and a demonstrated record of success in architecting and engineering desktop- and web-based software Expert grasp of Computer Science/Engineering stables such as data structures, data modeling, algorithms, distributed systems and software design Expert knowledge developing and debugging in Python and/or Java Familiarity with scientific programming languages like R and Matlab a plus Proficiency at querying SQL and NoSQL databases and ability to build and maintain processes to pull & integrate data from various sources Track record of solving ambiguous and complex technical problems Be able to act independently but also create collaboratively Facility with working in geographically distributed teams Excellent organizational, written and verbal communications skills Strong critical thinking and attention to detail 57 Master Thesis Machine Learning Resume Examples & Samples . Literature review, identifying relevant machine learning concepts and algorithms Analyze available network traffic dataset and/or generate suitable data sets Implement the machine learning concepts in prototypes Analyze the performance of the new concepts and compare with existing concepts MSc studies in Computer Science or similar area Excellent skills in programming languages (Java, Python or Scala) Excellent skills in data analytics and machine learning Knowledge about big data platforms such as Hadoop and Spark Like to build end to end prototypes and concepts Be fluent in English 58 Software Engineer Emerging AWS Machine Learning Platforms Resume Examples & Samples . Bachelor’s or Ph.D degree in Computer Science or equivalent work experience 10+ years professional experience in software development of multi-threaded, scalable and highly-available distributed systems Experience with highly distributed, multi-tenet systems with clear state-full/state-less boundaries Experience with experimentation and statistics 59 Machine Learning Software Dev Engineer Resume Examples & Samples . BS, MS in Computer Science with 5+ years of relevant work experience Computer Science fundamentals in algorithm design, complexity analysis, problem solving and diagnosis Proficiency in, at least, one modern programming language such as Java, Python, C/C++, C#, Perl Communication: Can translate your thoughts to words and effectively communicate them Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations 60 Software Development Engineer Emerging AWS Machine Learning Resume Examples & Samples . Bachelor’s /Master’s in Computer Science with 5+ years of hands on experience in software development, including experience leading design and implementation of complex software projects Proficiency in multiple scripting languages (Python, JavaScript, ruby, etc.) Deep understanding of distributed systems and web services technology Knowledge of Machine Learning/Deep Learning algorithms Experience working with REST and RPC service patterns and other client/server interaction models PhD in Computer Science or equivalent technical expertise 61 Software Engineer Big Data, Machine Learning Resume Examples & Samples . Develop and improve Machine Learning based systems for solving hard problems Contribute to solving Machine Learning solutions for a broad variety of teams across Amazon Architect, Design, and Develop services, making them more maintainable, easy to use, and operationally sound Improve and extend existing applications, develop ETL logic, perform feature engineering, implement new machine learning and graphing algorithms Work Hard, Have Fun, Make History Bachelor's degree in computer science, computer engineering, or related technical discipline 5+ years development experience Solid understanding of algorithm design, problem solving, and complexity analysis Proficiency in at least one modern programming language such as Scala, Java, C#, C++, C , or Ruby/Python/Perl Strong design skills with understanding of common design paradigms Masters degree in Computer Science Expertise in Hadoop ecosystem (Spark, MapReduce, Hive, Beam, etc.) Core competencies in Scala, Java, REST, and JSON Deep understanding of web services software architectural and design issues Experience with cloud computing technologies 62 Software Development & Machine Learning Internship Resume Examples & Samples . Use computer vision and machine learning techniques to create scalable solutions for Amazon problems Implementation and evaluation of highly innovative computer vision algorithms Working closely with research teams Tracking general business activity and providing clear, compelling management reporting on a regular basis A MS in Computer Science, Statistics, Operational Research or in a highly quantitative field 3+ years of C++ or Python development experience Communication and data presentation skills 1+ years of industry experience in software engineering Basic Image Processing and Computer Vision Knowledge 63 Manager, Machine Learning Resume Examples & Samples . Deep theoretical knowledge and hands-on experiences in speech recognition, natural language understanding and machine learning. Breadth of knowledge in multiple speech and natural language areas Solid research track record with peer-reviewed publications in top academic conferences and journals in the related areas PhD Project management experience desired for working on cross-functional projects Experience in building complex, real-time software systems involving speech recognition & natural language algorithms that have been successfully delivered to customers, preferably on mobile devices Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations Ability to rapidly prototype and evaluate customer applications and interaction methodologies 64 Software Dev Manager, Machine Learning Resume Examples & Samples . Working with cross functional teams within Amazon including software development, user experience design, machine learning scientists, technical program management, and product management to develop detailed and creative solutions to complex problems, while keeping a watchful eye on timelines and costs Develop an understanding of the recommendations ML space to represent the team across many stakeholders Strong analytical and quantitative skills; strong bias towards data-driven decision making Implementation orientation; demonstrated ability to translate strategic differentiators into detailed product requirements Technical fluency; comfort understanding and discussing architectural concepts, schedule tradeoffs and new opportunities with technical team members Communicating with senior leadership about product direction, launch strategy, key success metrics and new opportunities BS in Computer Science, Mathematics, or a related field 3+ years of coding experience in Java, C++, and Perl 2+ years of relevant experience as a Software Development Manager Delivered features for at least one large scale production system Experience managing efforts in Unix/Linux environments, distributed systems and/or applications of Machine Learning technologies MS in Computer Science, Mathematics or a related field and/or 5+ years software development experience 5+ years of relevant experience as a software development manager Expertise in recommender systems and/or machine learning Experience working with extremely large datasets, using tools such as Spark, Hadoop Experience in a startup environment A proven track record of software delivery through all phases of development A proven track record of hiring and developing careers of software engineers Knowledge of software engineering best practices including coding standards, code reviews, source control management, build processes, testing, and operations Experience with building complex, highly scalable software systems that integrate with predictive models or machine learning applications 65 NLP & Machine Learning Senior Software Engineer Resume Examples & Samples . MSc/BS or higher degree in computational linguistics or computer science At least 3 years experience in the areas of natural language processing, information extraction and machine learning Experience in one of the following NLP domains: anaphora resolution, question answering, textual entailment, named entity recognition, dialog generation Experience in one of the following machine learning domains: deep learning, sequence learning, learning to rank, feature selection, recommender systems Publication record in research conferences and journals Hands-on experience with NLP and machine learning libraries (e.g., scikit-learn, Factorie, Weka, MALLET, Stanford NLP) Experience with ontologies, entity modeling, and semantic web technologies At least 4 years experience using an object-oriented programming language (C++, Java, Scala) and scripting languages (Python) Experience in developing large software systems Experience in developing Web-based applications 66 Big Data & Machine Learning Resume Examples & Samples . Demonstrate experience with QA in a big data environment, with knowledge of Hadoop, Hbase, spark, kafka, and akka a plus Demonstrate extensive hands-on experience with test automation tools and platforms Demonstrate experience in formulating holistic QA approaches, from unit testing through to end-to-end system testing Demonstrate previous QA experience in an agile development environment with – at least – weekly deliveries to production Appreciate and understand the cloud delivery model and how that affects application solutions – both delivery and deployment Solve problems in robust and creative ways and demonstrate solid verbal, interpersonal and written communication skills Work in an environment with a significant number of unknowns – both technically and functionally. Inherent in such a new venture Collaborate across all teams in the group, from product managers and data scientists, to product engineering and release Work globally in a geographically dispersed team Demonstrate at least 10 years experience in test engineering with at least 5 years in test automation 67 Machine Learning Technology Consultant, Mid Resume Examples & Samples . 4+ years of experience with computer architecture design and related research and development Ability to commute to Arlington, VA MA or MS degree Experience with simulation and training of supervised, unsupervised, and reinforcement learning algorithms Experience with government-sponsored research activities Experience with program management Knowledge of implementation of machine learning algorithms in architectures, including deep hierarchical artificial neural networks Knowledge of probabilistic computing, low precision computing, and Bayesian inference Knowledge of the current state-of-the-art in hardware implementations, including CPU and GPU for training and execution learning algorithms Ability to convey complex technical insights to specialists and generalist audiences MA or MS degree in EE, Computer Engineering, CS, or related field preferred; PhD degree a plus 68 Senior Engineer Machine Learning Resume Examples & Samples . Lead the development of LG's next generation scalable machine learning platform. Develop in-house platform solutions involving deep learning frameworks and optimizations to ML algorithms to help contribute to a number of key advanced technology and innovation projects that LG Silicon Valley Labs (SVL) is focusing on. This requires core expertise and prior experience with machine learning projects Evaluate, modify and maintain LG's implementations and forks of open source deep learning frameworks. Examples of open source deep learning frameworks include Tensor-Flow, Theano, Torch7, Café, Cuda-Convnet. Contribute towards both proprietary (LG internal) as well as upstream improvements to these frameworks Add wrappers and service APIs around core deep learning frameworks to allow webOS platform to do either device intensive or cloud based computations around training of data sets or execute built-in classification models on device Develop and customize AI/machine learning solutions towards real customer facing projects such as vehicles, signage, TV, and around relevant technologies like computer vision, NLP, handwriting analysis, video content recognition, gesture analysis, and various other relevant applications for the LG platform group at SVL Be a great team player. Teach other team members about new and groundbreaking work happening in the field of deep learning Deliver projects with high quality on time LI-SB1 69 UI / UX Engineer, Applied Machine Learning Resume Examples & Samples . Expertise in Javascript programming Expertise in a popular open-source Javascript framework like AngularJS or ReactJS Expertise in popular charting and visualization frameworks like D3.js Deep interest in user interfaces and design as well as software development and effective programming methodologies Strong Object-Oriented Programming skills Strong Unix/Linux skills 70 Machine Learning Resume Examples & Samples . Experience using and developing machine learning or statistical algorithms Excellent understanding of mathematical underpinnings of the algorithms Good C/C++ skills Highly professional, with the ability to deliver solid work on tight schedules Knowledge of R / Matlab / Mathematica is highly desirable 71 Core OS Machine Learning & Differential Privacy Engineer Resume Examples & Samples . At least 2 years practical experience in using and developing privacy preserving machine learning or statistical algorithms Proven track record of delivering concrete implementations Excellent understanding of mathematical underpinnings of machine learning and data privacy Knowledge of Python / R / Matlab / Mathematica is highly desirable 72 Machine Learning Infrastructure Engineer Resume Examples & Samples . Proficiency in C++ and Python Excellent understanding of abstraction and modularity Ability to master new concepts and technologies rapidly Strong analytical skills and ingenuity Deep technical understanding of the candidate's own work as well as the works of others Excellent ability to explain technical ideas to others in a clear and concise manner Passion for assimilating and extending the state of the art in multiple research domains (ideally including fields such as compilers, programming language design, distributed systems, and machine learning) Strong commitment to the core values of Apple, ensuring the absolute highest standards of quality, innovation, scientific rigor, and respect for our customers and their privacy (Optional, but very helpful) Experience with compilers and programming language design (Optional, but helpful) Experience with functional programming and/or formal methods (Optional, but helpful) Experience with Metal, CUDA, or OpenCL (Optional, but helpful) Experience with distributed systems (Optional, but helpful) Familiarity with basic concepts of machine learning 73 Software Engineer, Applied Machine Learning Resume Examples & Samples . The position requires a solid knowledge of secure coding practices and experience with open source technologies Strong Object Oriented Programming skills and proficiency in languages like Java/C++ Experience in distributed systems, design and implementation of high throughput, low latency applications Solid CS background, concurrent programming, and data structures Solid understanding in NoSQL technologies like Cassandra Solid understanding and working knowledge on Hadoop Deep understanding of TCP, websockets, and libraries like Netty Excellent problem solving skills, critical thinking, and communication skills Strong ability to learn new technologies in a short time 74 Machine Learning Platform Engineer Resume Examples & Samples . 5+ years of experience working on data and ML projects Strong understanding of statistics and applications as well as strong working knowledge of machine learning & deep learning techniques, including hands-on experience with corresponding software libraries and frameworks Experience with NLP, image classification is a plus Exposure to GPU based deep learning is a plus Experience in Apache Hadoop, Spark or other MR frameworks is required Strong programming skills in Java, Python and/or Scala are expected Demonstrate ability to analyze a problem, and to develop & engineer a full solution from concept to deployment to production Team player with long term vision and willingness to take lead in supporting the overall team goal is a must Strong interpersonal, written, and verbal communication skills are required to present own results to other teams in a meaningful & engaging way 75 Machine Learning Lead Resume Examples & Samples . Experience in using machine learning techniques for classification, regression, or ranking problems Experience in building predictive models for recommendations or personalization Design and implementation of shipping, innovative consumer products Minimum of 5 years experience building large-scale consumer facing software Experience with search or indexing is a plus Experience with deep learning and neural networks is a plus Experience in compiled languages C, C++, Objective-C, or Swift is a plus 76 Recruiting Manager, Machine Learning & AI Resume Examples & Samples . 3+ years of leadership experience guiding recruiting teams in an environment Experience managing teams of 15+ direct reports Experience growing and developing a range of talent at different stages of their career Strategic thinker with data analysis and analytical skills 77 Machine Learning & Graph Theory Postdoc Resume Examples & Samples . Graph theory and graph algorithms Data intensive computing High-performance computing Advanced programming skills Background or research-level expertise in as many of the following: dynamic graph algorithms, high-performance computing, discrete optimization, algorithm engineering, data-intensive computing 78 Machine Learning Resume Examples & Samples . Proven achievements in machine learning research Ability to read, understand, and communicate technical documentation Software development experience in machine learning and natural language processing such as Python, R, Matlab, etc Strong background in Python, SQL, and R. Familiarity with designing and conducting experiments with human subjects 79 Senior SDE, Machine Learning Resume Examples & Samples . Build scalable, high-performance software for productionalizing recommendations models Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key features and processes Establish scalable, efficient, automated processes for large scale data analyses, model development, validation and implementation Research and use statistical techniques to create scalable solutions for business problems Work closely with scientists and engineering teams to create and deploy new features Work closely with stakeholders to optimize various business operations Track general business activity and provide clear, compelling management reporting on a regular basis Ability to lead and mentor engineers BS + 2 years of experience in software development, or MS (in CS or related field) 5+ Years of experience in Softfware Development Experience building high-quality scalable production software Familiarity with many development languages: C++, Java, Python, expert in at least one Experience with full development life cycle for large-scale software products including experience with service oriented architectures, design patterns, web services, and web applications/services development 1+ years of experience applying machine learning to solve real-world problems Experience working with Spark, Hadoop, and AWS (EMR, EC2, S3, etc…) Experience working with CUDA and GPU programming Experience building high-performance computational software Experience working with large volumes of real-world noisy data 80 Machine Learning / Computer Vision Engineer Resume Examples & Samples . MS or PhD in Machine Learning, Computer Science, Robotics, or equivalent technical field preferred Completed end-to-end machine learning algorithm deployment expertise – including ETL and data quality analysis (academic or industry experience) At least one year experience(academic or corporate) implementing machine learning algorithms on multiple platforms Fast prototyping skills Strong knowledge of feature engineering and trade-offs between various machine learning algorithms Experience developing deep learning models using tools such as Caffe, Tensorflow, Theano, or similar tool At least one year experience(academic or corporate) programming in Python/R or C++ (preferably both) At least one year experience(academic or corporate) with revision control software (Git preferred) and related development best practices Understanding of code documentation and unit testing Familiarity with database development/application integration Experience with signal processing and time-series data analysis Experience with code parallelization/optimization including GPU programming Creative/original thinker 81 Ensemble Machine Learning Intern Resume Examples & Samples . Must be a junior in an undergrad program or higher, with a minimum 3.2 GPA (will be verified) Preferred course of study: Computer science, Must have solid knowledge of machine learning methods, big data technology stack including Apache Spark, bioinformatics exposure Demonstrated ability to review scientific publications Ability to be self-directed and work well in a fast-paced environment is essential Must have strong communication skills and ability to work effectively in a collaborative environment 82 Technical Sourcer, Machine Learning Resume Examples & Samples . 4+ years hardware and software sourcing experience with a search firm or in-house recruiting team Experience working with and building sourcing strategies with Director level hiring managers Experience sourcing in the machine learning space is a big plus Good eye for talent with ability to quickly screen resumes to identify fit Excellent research/sourcing skills with ability to dive deep into searches for hard-to-fill reqs Sound candidate engagement approach with ability to activate passive candidates Sharp interview skills Solid tech and industry knowledge with ability to understand relevant tech skills, target companies, conferences, open source communities Strong interpersonal skills with ability to communicate well Passionate about Facebook and our mission with the ability to convey this to candidates 83 Machine Learning Expert Resume Examples & Samples . PhD in one of the machine learning related fields: deep learning, graphical modelling, learning to rank, data mining and web mining. Postdoctoral work highly desirable Strong programming skills, at least being efficient with one low level language, C++/Java, and one of scripting languages Python/R/Scala Proven experience of working with real data (data cleaning, data visualisation and modelling) (can include time in academia/research) 84 Executive Assistant to VP, Machine Learning Resume Examples & Samples . 5+ years work experience in a fast-paced executive administrative capacity Strong skills in key programs including Microsoft Outlook, Word, Excel and PowerPoint High level of integrity and discretion in handling confidential information Demonstrated creative problem-solving skills Prior experience in a fast-paced, high-tech company Experience working with SharePoint Desire and aptitude for learning new concepts on the job Experience working with a Global team Experience working with a Technical team 85 Machine Learning Researcher Resume Examples & Samples . 1-4 years of related experience Superb analytical and quantitative skills Demonstrated interest in financial markets 86 Machine Learning Intern Resume Examples & Samples . Enthusiasm for applying Machine Learning to business problems Computer science grounding in a range of algorithms and data-structures Proficient in an object-orientated programming language (Java, C++, C#, Python, etc.) Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly in both verbal and written form Postgraduate study 87 Senior Engineer, Machine Learning Resume Examples & Samples . Design and develop a cost effective machine learning & statistical model for Predictive and Prescriptive Analytics applications Plan, create, coordinate, and deploy business information solutions Work with peers and business partners to gather business requirements and define technical specifications and plan for developing and deploying solutions Design and setup online A/B tests Master’s degree in Computer Science, Computer Engineering, Mathematics and, or Statistics; PhD is a plus Experiences in making engineering & business trade off decisions based on statistical analysis and insights Familiarity with open source tools e.g. HDFS, SQL, Hive, Pig, Spark, Scala, Java, Python, etc Familiarity with machine learning packages e.g. Weka, R, Scikit-learn, Scala/Spark, Mahout, Vowpal Wabbit, etc Willingness to drive results and to push the boundaries by taking justifiable risks with management supports Experience with Google, Azure, AWS platforms, Apex/VisualForce, a plus Excellent verbal and written communications skills 88 Machine Learning Software Engineer Resume Examples & Samples . A passion for solving real world problems with machine learning BS in Computer Science, Math or related field. Advanced degree preferred Experience working with collaborative filtering, clustering, classification, regression, and/or statistical modeling Knowledge of Hadoop, Hive, Redshift or other big data tools Knowledge and experience of SQL and relational databases Fluency with statistical tools such as R or Python scikit-learn Strong computer science fundamentals (data structures and complexity) 89 Business Developer for Machine Learning Development Resume Examples & Samples . Stay connected to customers, customer councils, end users and SAP ecosystem to ensure grass-root level understanding of their current & future needs Ability to capture customer requirements and translate them into software specifications Build business cases to implement solution strategy Contributes to the efficiency, effectiveness and improvement of processes Develop/build story boards for demos of innovation solutions Monitor and analyze technology and industry trends, market research data and customer requirements to identify growth opportunities for SAP Develop and drive solution roadmap and corresponding revenue plan. Build business cases to implement solution strategy Deliver high quality solutions (packages), validation and acceptance of planned and implemented scope adding solution-related non-coded assets and services Create roll out materials e.g. collaterals, references, success stories Actively participate in customer communities. Support strategic deals and customers and partners At least 5 years of solution/business development experiences Experience in develop co-innovation user case with customer Excellent English language skills Ability to travel domestically and internationally Advanced degree in Computer Science/Math/Engineering; MBA preferred 90 Frontend Developer for Machine Learning Development Resume Examples & Samples . As a Frontend developer you will be responsible to design and implement complex UI features using JavaScript, HTML5, SAPUI5 and mobile technologies Build robust and scalable solution bringing in some of the industry’s software engineering best practices Work with UX designer, cross functional teams and collaborate with other teams to develop scalable and robust solutions BS or MS in Computer science with experience in developing frontend applications Hands-on skills in web app development with expert level knowledge of CSS, HTML5, JavaScript, SAPUI5 and JSON/XML/OData manipulation Be able to demonstrate skills to personal projects, GitHub repository, and open source contributions Experience creating mockups with Sketch or Illustrator NodeJS, Python, Java programming experience Experience working with Redis, Mongo DB Knowledge in Bootstrap, Foundation Frameworks, SAPUI5, jQuery, AngularJS, React, Manipulating SVG with D3, Raphael or ChartJS 91 Senior UX Designer for Machine Learning Resume Examples & Samples . Experience with web development for desktop UI Experience as a leader of multi-disciplinary creative teams Experience building teams from scratch Experience defining a team's and v1 product vision Experience working with remote teams Experience working with research oriented teams Experience with machine learning technologies Experience presenting to senior leadership (VPs, SVPs) 92 Software Eng., Machine Learning Resume Examples & Samples . Create the technology future of online classifieds in a scalable, clean way Improve our applications and APIs to become better and smarter each day Leverage machine learning technologies for insight-driven improvements of our product Ensure code quality and maintainability by improving build and test systems Be an interface between Product Management, Design, Business and Customers Drive your own ideas for code and process improvement and achieve the next level together with the team Be involved in the whole development lifecycle from architecture to QA and deployment 93 Product Specialist for Machine Learning Incubation Team Resume Examples & Samples . Master’s degree in computer sciences or related field Excellent product and business expertise in sales and service solutions, e.g., CRM or SAP Hybris Cloud for Customer Ability to work in a global team with distributed stakeholders and team members Deep understanding of customer needs as well as long-term interactions with customers Proven experience in planning, executing and coordinating development projects People and Project management skills Experience in applying Design Thinking Excellent English language skills, German language is a plus 94 Software Engineer, Machine Learning, Building Resume Examples & Samples . Adapt machine learning techniques from domains such as Vision and Speech to build intelligent user experiences Develop optimized software to run on variety of platforms and environments including mobile, tablet and laptops M.S. or Ph.D in Computer Science and 3+ years of relevant work experience 3+ years of experience in applying machine learning techniques to computer vision and speech recognition domains Experience with scripting languages such as Perl, and Python 95 Lead Machine Learning Software Engineer Resume Examples & Samples . Progressive SOA based solution design Utilize data from several data sources to support solution features Develop and deploy solutions independently and as a team member Direct the work of other development resources 3+ years of experience leading and mentoring technical team members 5+ years of experience with the fundamentals and practical application of Machine Learning & Al 3+ years of experience with one or more of the following Machine Learning and Cognitive technologies: IBM Watson, SAS, Amazon ML, Google Cloud ML, Azure ML Studio Proficiency with core Machine Learning methodologies: Regression, Classification, Clustering, Matrix Factorization, Predictive Analytics, Natural Language processing, Decision trees, Support Vector Machines, Neural Networks/ Deep Learning 3+ years of experience creating prototypes in R, Python, Scala, Java or similar stack 3+ years of experience with data retrieval and manipulation utilizing: SQL, Hive QL, Python, Hadoop, R, Unstructured Data Ability to work effectively in a cross-functional team Demonstrated initiative and strong ownership of deliverables Experience with service oriented architecture 96 Director of Machine Learning Software Engineering Resume Examples & Samples . Provide leadership and direction setting for an Engineering group responsible for delivering software solutions that embody Cognitive Computing and Machine Learning Capabilities and Features Insure the delivery of progressive SOA based solution designs Drive resources to leverage existing frameworks and standards, contribute input for improving existing ones and support the creation of new where they do not exist Direct the work of others 5+ years of leadership experience (including leading and mentoring technical team members, and budget responsibility) 5+ years of service development (REST, API, Microservices) Thorough understanding of core Machine Learning methodologies: Regression, Classification, Clustering, Matrix Factorization, Predictive Analytics, Natural Language processing, Decision trees, Support Vector Machines, Neural Networks/ Deep Learning 3+ years of experience with retrieval and manipulation processes utilizing: SQL, Hive QL, Python, Hadoop, R, Unstructured Data Advanced degree in computer science or related field (PhD desired) Healthcare experience 97 Automated Driving Research Intern Machine Learning Embedded Software Resume Examples & Samples . Development of software toolsets for acquisition, data processing, and visualization of large-scale data sets Simulation studies, including Hardware-in-the-Loop scenarios Code optimization to migrate prototype algorithms to automotive/embedded systems Participate in technical discussions and in the creation of new ideas for automotive applications within the existing autonomous vehicle research team Publish technical reports, papers and/or pursue Intellectual Property rights Bachelor's degree in Engineering or Computer Science 3+ months of experience programming in C/C++ Demonstrated ability to carry out independent research and lead projects Proficiency in multiple operating systems such as Windows, UNIX, Linux, etc Proficiency in multiple contemporary computer programming languages and environments such as C/C++, PERL, Python, Java, OpenGL, OpenCV, CUDA, MATLAB etc GPU, GP-GPU, Parallel programming tools and language extensions etc Experience with hardware such as LIDAR, radar, cameras, GPS, IMUs, CAN bus, etc 98 Senior Manager of Machine Learning Resume Examples & Samples . Develop and manage the long-term vision and portfolio of research initiatives for your team Lead experienced scientists as well as develop junior members from academia/industry to a successful career track in applied science PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent) 10+ years of practical experience applying ML to solve complex problems for large-scale applications 5+ years of practical experience managing one or more machine learning teams Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes Track record of hiring and leading experienced scientists as well as a successful record of developing junior members from academia/industry to a successful career track 10+ years of practical experience applying ML to solve complex problems for applications handling gigabyte and terabyte size datasets Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval Track record of scientific publications in premier journals and conferences 8+ years of practical experience managing one or more machine learning teams Professional experience in software development (software design and development life cycle) Project management experience for working on cross-functional projects 99 Machine Learning Product Manager Resume Examples & Samples . Manage machine learning & big data projects to solve strategic problems of different business groups at Intel (e.g. Design, Manufacturing) Lead a project team of ~5 product analysts, big data developers and data scientist from early opportunity exploration stages to agile solution development Serve as a Product Manager of the various projects, define project scope, vision and priorities Work with senior stakeholders to ensure and define project success and growth Business development: from finding new ideas for machine learning based projects, through analyzing them to growing them into a valid opportunity for a project 100 Software Developer, Machine Learning Resume Examples & Samples . Develop and Implement predictive models for real time predictions Boost Innovation by building rapid prototypes for experimentation Use statistics, NLP and machine learning techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of both structured and unstructured data to help automate and optimize key processes Design, experiment and evaluate highly innovative models for predictive learning Work closely with business staff to optimize various business operations A Masters' degree in Computer Science 2+ years of software engineering experience Strong coding ability using Java/Python Strong business problem solving ability Experience with UI – Web and mobile development 1+ years of hands-on experience in predictive modeling and large data analysis Proficiency in object-oriented design 101 Machine Learning Software Engineer Resume Examples & Samples . Develop scalable algorithms to optimize and monitor campaign performances across a diverse group of over 20,000 marketers Design and run experiments to optimize user segmentation, creative design, campaign setup, and real-time bidding strategies Apply statistical models on large datasets to BS or MS (PhD preferred) in a quantitative field such as Statistics, Quantitative Finance, Computer Science, Physics or a related degree. Relevant work experience will supersede degree 2+ years “hands-on” experience building production-ready, scalable software solutions 3+ years experience in building models and developing algorithms for machine learning, statistics, and simulation in industry and/or academia 3+ years experience with Python. Familiarity with R is a plus Strong SQL skills Excellent communication, organization, and problem solving skills Link or attachment of code you’ve written related to a recent data analysis. Please provide an overview of your key findings, methodology and impact 102 Machine Learning Intern Resume Examples & Samples . Working with Hadoop, Redshift, and other big data systems Applying machine learning techniques to personalize the site experience for our users Building algorithms to help our review fraud team catch bad guys Working on various classification and regression problems over our huge database of traveller reviews and site data 103 Software Engineer, Core Machine Learning Resume Examples & Samples . Minimum of 2 years recent Java or Scala application development experience Expert with practical experience in Object Oriented Design Deep experience in a wide range of APIs, tools, and open source libraries Strong SQL skills required Experience in distributed data processing frameworks such as Spark and Hadoop Intermediate Linux/UNIX skills An undergraduate in computer science (or related field) Graduate degree in computer science Expertise with Hadoop and Spark Experience building web UI with React 104 Product Manager, Payments Machine Learning Resume Examples & Samples . Develop and communicate a bold vision for the product. Write PR FAQs, work backwards to improve the customer experience Own the product roadmap and prioritize the engineering and optimization projects Launch new channels and drive improvements in optimization Communicate regularly with stakeholders to ensure product roadmap meets their business needs Insist on highest standards for content and offers Write the requirements for launching on Alexa, reach new customer segments, etc Bachelor’s degree in Computer Science, Mathematics, Economics, Statistics, Finance or related technical field 5+ years of relevant employment experience, including bringing product features to market Demonstrated ability to engage and influence people and teams at every level in the organization Strong verbal/written communication skills to work effectively communicate with both business and technical teams Proven track record of using analytical and quantitative skills to help propose successful changes in optimization, forecasting or similar decision making algorithms An MS degree in Computer Science, Mathematics, Statistics, Finance, Machine Learning or related technical field or MBA from a top university Experience in econometrics, statistical modeling and machine learning methodologies Python, SAS, SQL, or other relevant scripting language Experience in display advertising or online marketing 105 Machine Learning Resume Examples & Samples . Research and develop deep learning algorithms Stay current with DL and ML latest research and technology ideas Provide SW specifications, production quality code and engage with algorithm proliferation activities Research and develop state of the art techniques in the field of computer vision, ML and DL Work with the system, physics, SW and application group 106 Machine Learning Researcher Resume Examples & Samples . A Masters’ degree with several years’ experience and a view to completing a PhD, or a minimum of PhD (with research in machine learning algorithms) if coming straight out of education Experience in Python or R Exposure to Spark/Hadoop and either Theano/Tensorflow/Caffe/Torch Mastery of relevant mathematics for machine learning such as linear algebra and gradients Ideally you may have a mathematical background in Cognitive Science, Deep Learning, Advanced Semantic Design, Information Extraction, Information retrieval, Probabilistic Decision Marking, or similar 107 Machine Learning & Data Exploitation Postdoc Resume Examples & Samples . Strong mathematical background (e.g., in probability, statistics, machine learning, signal processing, and/or image processing) Practical technical programming experience An enthusiasm for creative problem solving The ability and desire to work as part of a multi‐disciplinary team 108 Avp-machine Learning Resume Examples & Samples . Be a key stakeholder in enabling Predictive Modeling Solutions for domain specific products using standard industry best statistical Algorithms Define Data Preparation Approach, design model and finalize the appropriate Machine Learning Algorithms based on Problem Scenario. Handle Data Munging/ Data wrangling/ Mash up Techniques to prepare sample, test data Apply data mining techniques, do statistical & exploratory analysis and build high quality prediction systems integrated with existing products Help/coordinate with, other date scientist’s or ML programmers to evaluate algorithms and fine tune the models Work with Product Managers to understand the Predictive Modeling requirements and Define the Architecture using R, Python, Spark, SQL, Hive, Mahout, Tableau ..etc Identify the Supervised/Un Supervised classification, Regression, Rule and Cluster based Statistical Machine Learning algorithms which fit to the required data analysis Selecting features, building and optimizing classifiers using machine learning techniques Work with Technical leads to design, build optimized solutions on par with current industry best practices in Processing, cleansing, and verifying the integrity of data used for analysis Handle large volumes of data for sample data preparation and test data preparation to apply the ML models using Data Munging / Data wrangling/Mash up Techniques Provide consulting and support for custom development and quality assurance efforts for custom work Provide best practices on R, Spark, Hive,SQL, Python,Tableau and other others Manage development designs across multiple projects to meet project and customer required time lines Define Exploratory Data analysis Approach to analyse data and summarize their main characteristic with visual methods Proven track record in ML & Predictive analysis using Technologies like R,Spark,Python,Mahout.Hive etc Sound knowledge of Statistical Machine Learning Algorithms for exploratory & predictive data analysis Comfortable in a dynamic atmosphere of a technical organization & well versed with object oriented languages, database design & hands-on experience in writing codes, technical design, architecture reviews & large scale enterprise applications Candidate must be organized and analytical, adept at working in a multiple team’s environment, able to design and implement a technical solution, and able to handle multiple priorities in a fast moving environment Experience in Regression, Classification, Clustering Algorithms like Linear Regression, Random Forrest, Decision Tree, Logistic Regression, K-Mean, Naive Bayes, SVM, Decision Forests, etc B.Tech / M.Tech /BE in Computer Science, Software Engineering, MIS or equivalent preferred Should have hands-on expertise in some of the following technologies: R, Python, Spark, Mahout,Hive..etc 109 Principal Machine Learning Engineering Manager Resume Examples & Samples . Identify and attract top talent Build relationships and be a trusted advisor across complex distributed systems Analyze and take decisions based on complex and ambiguous data points Identify, build and coach the team on ML techniques to solve technical problems Build user funnels to better understand opportunities Identifying third party data tools, driving selection and adoption Development and implementation of experiences to drive new experiences across Bing 110 Machine Learning & Computer Vision Architect Resume Examples & Samples . Expertise and experience in machine learning algorithms, such as convolutional neural network, LSTM (Long Short-Term Memory) neural network, classification/detection, reinforcement learning and their applications Familiarity in computer vision algorithms such as object detection, tracking and recognition, 3D computer vision — SfM/SLAM Strong programming skills in C++ and Python. Knowledge of Matlab is a plus Knowledge/experience in HW architecture is a big plus Knowledge in image processing, camera pipeline is a big plus Knowledge in language/speech processing is a plus Strong communication skills and ability to work across various groups 111 DSP Engineer Wireless / Machine Learning Resume Examples & Samples . Experience with machine learning algorithms, deep convolutional neural networks (DCCN) Implementation of DCCN in software and/or hardware (ASIC) Implementation of complex signal processing on at least one of the following platforms: FPGAs, ASIC, ASSP, GPP, GPU, DSP 112 Graph Analytics Machine Learning Senior Researcher Resume Examples & Samples . Design and implement secure, scalable, graph-based, and fault-tolerant solutions across a distributed architecture, with the objective of researching and developing semi- and fully automated approaches applicable across multiple domains Bachelor's degree and 9+ years of related experience At least three years of specialized experience innovating analytical techniques and performing analytical functions using machine-learning libraries and approaches Advanced degree in computer science (Ph.D highly desired) or a related discipline. 8 years of overall experience is preferred Strong record of publication in Machine Learning, Artificial Intelligence, or related discipline Prior experience as a project lead, preferably as PI Familiarity with multiple approaches to representing and developing solutions using probabilistic graphical models (Bayes Nets, CRFs, MLNs, PSL) using techniques like statistical relational learning for problems such as causal discovery, temporal dependence, structure mapping and link/evidence prediction Familiarity with multiple state of the art approaches to machine learning (unsupervised, semi-supervised, supervised, transfer) and existing libraries for implementing these approaches (e.g., CUDA, Caffe, Theano, Torch, Nvidia Digits) Prior experience with a few of the following models: Logistic Regression, Linear Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Markov Logic Nets, Probabilistic Soft Logic 113 Machine Learning Expert for the Debating Technologies Team Resume Examples & Samples . Join a team of creative thinkers to build debating technologies that will help humans reason, make decisions, or persuade others Contribute to a team that is pushing the frontiers of intelligent systems Work closely with researchers worldwide to develop new ways to interact with computers Graduate degree with academic research and hands on experience in natural language processing and/or machine learning Programming knowledge and experience. Java is an advantage 114 Wireless Integrity Software Database & Machine Learning Resume Examples & Samples . Use statistical and machine learning techniques to help our products behave intelligently and delight the end user Design, development and evaluation of highly innovative models for predictive learning Work closely with software engineering teams to drive real-time model implementations and new feature creation Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation and model implementation Research and implement novel machine learning and statistical approaches Bachelor’s degree in Computer Science, Machine Learning, AI/Robotics or related field Coursework in software development Experience in predictive modeling and analysis Master’s degree in Computer Science, Machine Learning, AI/Robotics or related field Skills with Java or C++, Perl (or similar scripting language), and/or Matlab Strong communication and data presentation skills 115 IBM Watson Machine Learning Resume Examples & Samples . Contribute to the architecture, design, implementation, and delivery of product Develop high quality, highly performance code Collaborate with the team to deliver product on time Strong object-oriented design skills and coding skills. Experience in Java, C++, Python, Scala or other equivalent languages Ability to write high performance production quality code Good data analysis, design and testing skills. Experience with Hadoop, Spark, or related technologies Excellent communication skills and teamwork Self-driven, innovative and collaborative Loves new technology challenges and learning new things Like to work in an agile, iterative, test-driven development team 116 IBM Watson Machine Learning Resume Examples & Samples . Architect, design and implement machine learning platform following design thinking practices Lead the development team to create high quality deliverables iteratively following agile process Provide technical vision on the product and technical guidance to the development team Strong skills and experiences in software architect Strong object-oriented design skills and coding skills. Ability to write high performance production quality code. Strong skills in Java, C++, Python, Scala or other equivalent languages Strong data analysis, design and testing skills. Experience with Hadoop, Spark, or related technologies Experience with building high-performance, highly-available and scalable software systems Knowledge of the latest advancements in the machine learning, AI technologies Ability to solve complex problems independently and to seek out and generate innovative solutions Self-driven, innovative and collaborative. Exhibit a high level of individual initiative and ownership Experience mentoring and training the engineering community on complex technical issues Ability to focus on delivering results in a dynamic environment with aggressive deadlines and multiple priorities Experience with agile, iterative, test-driven development 3+ years experience of software development lead 117 IBM Watson Machine Learning Resume Examples & Samples . Lead the definition and development of machine learning product UI architecture and framework Work with User Experience design to iterate and implement Web UI with high quality, simplicity and intuitive principles Provide technical leadership and mentoring for teammates Deep understanding of UI framework and choices, and experience in building UI applications Strong skills in writing clean, unobtrusive Javascript including experience with common libraries and debugging tools HTML5, CSS, SASS and semantic markup JavaScript frameworks (AngularJS/ReactiveUI) Javascript/JQuery AJAX Familiarity with the whole web stack, including protocols, web service and web server optimization techniques Strong skills in object oriented design and programming best practices Passion for shipping great software people actually want to use Love to constantly learn new skills and refine existing ones 118 IBM Watson Machine Learning Resume Examples & Samples . Work with product manager, designer and engineers to design and develop the product with data scientist best practices embedded Design and develop new algorithms and models for product improvement Improve the user experiences of all aspects of the learning process, include data collection to data processing, exploration, visualization and modeling Work with customers to identify real problem and scenarios, and apply product to improve business results Deep knowledge of statistics and data analysis (linear regression, statistical test, Markov chain, Bayesian analysis, etc) Good understanding of common families of models, feature engineering, feature selection and other practical machine learning issues, such as overfitting Experience in Python, Java, C++, Scala, or other equivalent languages/tools commonly, one of frameworks like SparkML, TensorFlow Knowledge of ML pipeline frameworks, incremental model building and scoring, detection of model decay is a big plus Experience working with relational databases and SQL, the ability to write complex SQL queries Open-minded, adaptive to changes, and excited to learn new things Strong team player, great problem solver Excellent communication to both technical and non-technical audiences Knowledge and experiences of big data and analysis techniques, e.g. Hadoop/Spark and/or other MapReduce paradigms is a plus Industry experience in building innovative end-to-end Machine Learning, Text analytics, search is a big plus 119 IBM Watson Machine Learning Resume Examples & Samples . Develop high quality, clear, maintainable code with functionality based on requirements Test the product to ensure full functional test coverage Good programming skills Java, C++, Python, Scala or other equivalent languages Good skills in computer science fundamentals in algorithm design, problem solving Knowledge in Hadoop, Spark, or related technologies Good communication skills and teamwork Self-driven, proactively and continually improve skill level and technologies needed in work Loves to learn new technologies 120 Machine Learning Expert Resume Examples & Samples . Data Science experience Programming skills: KDB/Q, Angular JS Expertise in any of: machine learning, Bayesian inference, time series analysis, forecasting, optimization Strong background in algorithms, mathematics and/or statistics Programming skills: Python, R, C++ or Java Interpersonal and communication skills Detail oriented attitude Be open to learn and apply new technologies and programming languages 121 IBM Watson Machine Learning Resume Examples & Samples . Measure, test and tune the performance of the product Identify, architect and implement software changes to improve the performance of the product Design and create tools to ease the job of profiling, analysis and performance tracking Strong understanding of machine learning, Good knowledge in Hadoop, Spark, or related technologies Excellent level of technical knowledge and understanding of whole system performance issues Experience in solving/optimizing real system performance issues, especially, experience in Spark, machine learning, Java application optimization work Good skills Java, C++, Python, Scala or other equivalent languages Strong experience in good software engineering practices MS/BS of Computer/Data Science or Engineering 122 Machine Learning Algorithm Developer Resume Examples & Samples . Research and develop state of the art Machine Learning algorithms Shoulder to shoulder work with the system, physics, SW and application group Provide SW specifications and production quality code on time to meet project mile stones Engage with customer facing activities to aid algorithm proliferation to customer sites 123 Machine Learning Postdoc Resume Examples & Samples . Experience in Materials Science and/or Geophysics Strong understanding of Mechanical behavior of materials under geologic loading conditions Proficiency in Python, Fortran, C, and C++ Excellent written and communication skills in English Significant code development experience and an understanding of computational methods Motivation to achieve in an independent work environment and also the communication skills to interact with a multidisciplinary, integrated team Code development experience Big data handling experience Experience with numerical modeling (e.g. finite element, finite difference, discrete elements) for simulating fault processes, or experimental background in fault physics is desired Solid understanding of materials science and or earthquake physics Excellent publication record in the field of materials science or geophysics 124 Machine Learning Research Engineer Resume Examples & Samples . MS or higher in the field of Math, Statistics or Computer Science with a focus on Machine Learning 3 years of work experience related to the above; or extensive experience working in these fields as part of a graduate or doctorate program Experience in parallel distribution of algorithms using platforms such as: Spark, Hadoop, etc Practical experience in developing high scale machine learning algorithms 125 Machine Learning Software Engineer Resume Examples & Samples . PhD or MSc degree in Computer Science, Mathematics, Physics, or related field Proficiency in at least one common programming language Strong design and development skills Proven track record of building applications to solve real-world problems Experience with machine learning and artificial intelligence Ability to tackle loosely defined problems Ability to explain complex topics in simple terms 126 WO Workalong Internship Machine Learning Resume Examples & Samples . Bachelor Computer Science or equivalent at WO level Programming skills Basic knowledge of neural networks and GPU computing Willingness to support others Able to read/write/speak in both Dutch and English Must show initiative, creativity, and ability to work independently Have a strong interest in IT and you like to work in a creative environment 127 Machine Learning for Autonomous Vehicles Research Engineer Resume Examples & Samples . Working closely with other researchers on enhancing, and testing, implementation of the existing machine learning algorithms for autonomous driving Creating and validating innovative machine learning based approaches Coordinating with fellow researcher engineers from the Ford engineering community in Dearborn, MI, Palo Alto, CA, Tel Aviv, Israel, and Aachen, Germany 1+ years' developing machine learning models such as using deep learning methods for classification and regression Experience applying machine learning approaches such as deep convolutional neural networks and/or recurrent neural networks Inquisitive, proactive, and interested in learning new tools and techniques Strong oral, written and interpersonal communication skills and an ability to work in a team environment Well-organized, independent and ready to work with minimal supervision Strong problem formulation and problem solving skills 128 Senior Machine Learning & AI Developer Resume Examples & Samples . Decision Management Development: You will need to be able to design, develop, and integrate decision management platforms either on premise at the client locations or via the Epsilon cloud working with engineering, database, and system administration teams. Below is a list of detailed responsibilities 5+ years of experience in marketing technology with an emphasis in decision management platforms such as; Oracle RTD, SAS Decision Manager, IBM Interact, or PegaSystems Decision Hub. Oracle RTD is preferred Experience using other decision management technologies is a plus. Examples: Adobe Target Automated Personalization, Infor Epiphany, Certona, SAP KXEN, Amazon and Microsoft machine learning platform Analytics background would be helpful; modeling and analytics experience highly valued Experience working with Oracle Java language needed (or equivalent), as well as background in database development Preferred domain knowledge around the following technologies; Oracle RTD, Blue Kai, Email Service Providers, Eloqua, Call Center environments, SFDC, and other CRM and Marketing Automation tools Other required skills in Microsoft Office (Excel, Project, Word, PowerPoint, OneNote, SharePoint, InfoPath, Outlook, Publisher, and Visio) Ability to manage and prioritize work across multiple projects, with different stakeholders, simultaneously Demonstrated verbal and written communication skills including technical writing / documentation, resource planning, as well as vendor management Background in Marketing Technology is highly preferred Bachelor’s degree required. Masters preferred 129 Senior PM for Machine Learning & AI Resume Examples & Samples . Manage Program/project scope, cost, quality and timeline deliverables Regularly report status to business and IT Preferred experience in Marketing technology solutions Preferred experience managing large programs and projects PM skills 130 IBM Watson Machine Learning Resume Examples & Samples . Work closely with UX designers to create fast, easy to use, reusable, testable UI components Test the UI components to ensure high quality and user experience Good skills and experiences in UI common libraries and debugging tools HTML, CSS Java Script frameworks (AngularJS/ReactiveUI) Good knowledge of web UI framework and choices, and experience in building web UI applications Knowledge of web-service and data-driven application architecture Self-driven, Love to learn new skills 131 Machine Learning Researcher / Developer Resume Examples & Samples . Bachelors with at least 5 years of experience, or 3 years with a Masters, or 0 years with a PhD within a Science, Technology, Engineering, or Mathematics discipline from an accredited college At least 4 years of research or work experience in deep learning techniques and frameworks Strong Background in Machine Learning (Deep Learning) Proficient in one or more programming languages such as MATLAB, Java, C++, or Python Familiar with one or more machine learning or statistical modeling toolkits PhD within a Science, Technology, Engineering, or Mathematics discipline from an accredited college Basic understanding of autonomy and artificial intelligence, including multi-agent systems, knowledge representation and reasoning, planning, plan recognition and decision making Experience with multi-player PC or consol gaming (e.g. Starcraft) Experience programming for GPUs 132 Director of Machine Learning Software Engineering Resume Examples & Samples . Provide leadership and direction setting for an Engineering group responsible for delivering software solutions that embody Cognitive Computing and Machine Learning Capabilities & Features Drive resources to leverage existing frameworks and standards, contribute input for improving existing ones and support the creation of new where they don't exist 3+ years of leadership experience (including leading and mentoring technical team members, and budget responsibility) 133 Senior Machine Learning Software Engineer Resume Examples & Samples . Knowledge of Hadoop, Hive, Redshift, Spark or other big data tools Proficiency in Java or C++ LI-RF1 134 Senior Research Engineer Machine Learning & Artificial Intelligence Resume Examples & Samples . Vehicle Network Systems Wireless communication Artificial Intelligence (AI) and Machine Learning technologies High competence in communication and networking Composing technical and research results reports and documentation Presenting technical result Interacting with stakeholders at different levels Fluent in English, spoken and written Technical competencies Sensor Fusion, Artificial Intelligence, Machine/Deep Learning Communication protocols IP, Cellular Network Protocols and Short Range Communication (802.11p) Embedded Software Development in C++ Linux, QT and generic development platforms To be successful we believe You need minimum 5 years of experience in development/integration of embedded real-time software 135 Data Analyst Machine Learning Resume Examples & Samples . You are responsible for the design and implementation of innovative technologies and algorithms from an idea to a software system Analysis and identification of new data related business opportunities in the manufacturing area (Internet of Things) are part of your job description You develop complex algorithms by utilizing modern approaches from the domains of machine learning and advanced data analytics in general You play a leading role in the interpretation and analysis of data from complex technical systems The identification of new technological advances and the development of own invention disclosures complete your field of responsibility You hold an University degree (PhD degree is a plus) in computer science, bioinformatics, mathematics, physics, or engineering sciences (thesis in the field of Machine Learning and especially Deep Learning is a plus) You already have 3 or more years of work experience and expertise with technologies, algorithms and methodologies in the areas of Data analytics and Machine Learning especially Deep Learning (publication record is a plus) Experience with project work in the research and development area especially in the domain of data discovery and data science is highly appreciated You have knowledge of and experience with modern analytical frameworks, libraries and analytical development frameworks You have experience with software development process and good programming skills in particular Python and Java combined with knowledge of analytical libraries, experience with Agile is a plus Advanced experience with massive parallel processing (Hadoop, Spark) and stream analytics (Storm, Spark Streaming) as well as relational databases is appreciated You have detailed knowledge of machine engineering, experience with control systems is a plus Advanced speaking and writing skills in English (German is a plus) complete your working profile 136 Machine Learning Engineering Lead Resume Examples & Samples . Design and develop effective machine learning & statistical model for Predictive and Prescriptive Analytics applications Work with peer technical leads, researchers, architects and product owner to gather business requirements and define technical specifications and plan for developing and deploying solutions Derive experiments to validate assumptions and hypothesis Perform proof-of-concept model for analyzing millions of user action records Analysis and present your discoveries and insights to your peers and management Mentor other developers on data mining and predictive analytics best practices 137 Senior Manager Machine Learning Expert Resume Examples & Samples . The position is located at client’s site in US Deliver high intensity projects in individual capacity Work on Machine Learning related projects Also, train the client team members on machine learning and advanced analytical techniques Someone who has built as well as implemented machine learning models 138 Machine Learning Research Engineer Resume Examples & Samples . Strong computer science and mathematics grounding, with knowledge of data structures, algorithms and computer architectures Hands-on experience with machine learning technologies. Examples include IBM Watson, Stanford’s DeepDive or Apache Spark Excellent communication, teamwork and leadership skills Experience with big data technologies such as Hadoop, NoSQL databases, etc Experience with natural language processing systems such as Google Prediction Experience developing production software in a corporate environment and/or delivering research prototypes to such organizations 139 R&D Manager, Machine Learning & Analytics Resume Examples & Samples . Ph.D. in Computer Science, Mathematics, Electrical Engineering or other relevant field with an emphasis on analytics, machine learning and/or artificial intelligence Experience in designing or adapting statistical analytics and machine learning for scalable high performance computing Proficiency developing in one or more languages such as C#, C++, Python or Java Experience developing productive relationships 3+ years of software research project management experience Ability to manage to deadlines multiple projects simultaneously Background in electronics and electronic test equipment Hands-on experience in big data technologies such as Hadoop, Apache Spark, NoSQL databases, etc 140 Machine Learning Researcher Resume Examples & Samples . Ph.D. in Computer Science, Mathematics, Electrical Engineering or other relevant field with an emphasis on machine learning and/or artificial intelligence Experience in designing or adapting machine learning for scalable high performance cognitive computing Hands-on experience with machine learning technologies. Examples include IBM Watson, Stanford’s DeepDive or Google Prediction Proficiency developing in one or more languages such as C#, C++, Python, MATLAB or Java Track record of innovation and research contribution as shown by peer-reviewed journal publications Self starting, requiring minimal supervision with strong problem solving skills 141 Machine Learning Senior Software Developer Resume Examples & Samples . Act as a point of contact for Machine Learning methods and tools, and lead their adoption in various security research teams Architect, develop, and integrate ML models to improve IBM-Trusteer's security protection for its clients (phishing detection, behavioral profiling, malware analysis, etc.) Implement proof of concepts for ML solutions to real-world cybercrime problems Measure and improve existing algorithms Graduate Degree in engineering, computer science or other technical related field At least 4+ years development & architectural experience in one or more general purpose programming languages Experience in machine learning algorithms and/or anomaly detection Strong statistical analysis and mathematical skills Solid understanding of the theory underlying Machine Learning algorithms and methods Independent, highly motivated and creative Dynamic and agile. Capable to adjust quickly to changing requirements, and the ability to deliver rapid & agile solutions Experience with one or more general purpose programming languages including but not limited to: Java, C/C++, Python, JavaScript, or Go Experience in backend development of large, distributed software systems Prior experience in the security domain Team management experience 142 Machine Learning Technology Consultant, Mid Resume Examples & Samples . Level decision Makers. Conduct background research to evaluate the feasibility and defense applications of new technological concepts. Produce and present findings and recommendations to a team of colleagues and clients. Assist with technical program management, program development, and briefing materials for government R&D efforts Ability to work in a Fast-paced environment Experience with government Sponsored research activities Knowledge of the current state The Art in hardware implementations, including CPU and GPU for training and execution learning algorithms 143 Machine Learning Team Leader Resume Examples & Samples . MSc in Electrical Engineering or Computer Science from a known university PhD in Electrical Engineering or Computer Science from a known university – an advantage 2+ years’ experience of managing Algorithm development teams 5+ years hands on experience as an algorithm engineer Deep knowledge of algorithm development technologies, methodologies Proven experience in Pattern recognition, Machine Learning and Deep Learning Experience in collaboration with Academy and companies- an advantage 5+ Matlab programming 5+ C++ programming 2+ Python programming 144 Director of Advanced Data Analytics & Machine Learning Resume Examples & Samples . M.S. or Ph.D. with specialization in one of the following: Advanced Data Analysis, Statistical Modeling, Machine Vision, or Machine Learning Minimum 10 years of relevant experience, including at least 5 years as Engineering-Manager in an Industrial setting Experience in a startup environment is desired but not required Proven track record of developing hi-tech innovative products embedding Advanced Data Analysis and Deep Learning technologies Proven experience in supervising and leading large teams of scientists and engineers to bring new innovative products and services to the marketplace Proven experience in doing hand-on engineering or technical work in the above desired fields Proven experience in growing a group by attracting and hiring tier-1 scientific and engineering talent 145 Senior Machine Learning Software Development Engineer Resume Examples & Samples . Responsible for the development and maintenance of key ML system features Will work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility Will work in an Agile/Scrum environment to deliver high quality software against aggressive schedules BS/MS in Computer Science or equivalent 7+ years of industry experience, including in machine learning projects Experience building scalable infrastructure or distributed systems for commercial online services Strong sense of ownership, customer obsession, and drive Mastery of the tools of the trade, including a variety of modern programming languages (Java, JavaScript, C/C++, Objective C, Python, Ruby) and open-source technologies (Linux, SQLite, OpenGL, Spring, Hadoop, Spark, Mesos, Rails) Experience developing machine learning software and an understanding of design for scalability, performance and reliability Sharp analytical abilities and proven design skills Experience in data modeling and analysis, especially with distinctive data sources Excellence in technical communication with peers and non-technical cohorts 146 Machine Learning Researcher Resume Examples & Samples . Strong academic and publication record Deep technical skills in machine learning, deep learning, computer vision, natural language processing, or artificial intelligence A passion for creating innovative techniques and making these methods robust and scalable Ability to explain and present deep technical ideas Creative, collaborative, & innovation focused 147 Manager, Machine Learning Resume Examples & Samples . Manage the day-to-day activities of the engineering team within an Agile/Scrum environment Hire and develop top-performing engineers Develop and execute on project plans and delivery commitments Work with business leaders to help define product requirements and with engineers to execute on them Build and maintain world-class customer experience and operational excellence for your deliverables 7+ years of relevant engineering experience 2+ years of people management experience Experience with OOD and object oriented languages Computer Science fundamentals (based on a BS or MS in CS or related field) Proficiency in at least one modern programming language such as C, C++, C#, Java, or PERL 148 Software Developer, Machine Learning Resume Examples & Samples . Develop research in machine learning applications Independently build, test and integrate various prototypes Manage both self-identified and assigned projects (planning timeline controlling budget and capacity, documenting project and process) Prepare and present projects status reports to BMW project partners and management both domestically and internationally Manage exploration projects with high-tech partner companies and BMW departments to quickly evaluate different ideas Identify, specify and arrange for purchase novel software and hardware tools required for development Because of the international development process, the ideal candidate will be comfortable working independently and effectively in a team environment and must have excellent communication skills and an attention to detail 149 Team Lead-machine Learning & Scalable Computing Resume Examples & Samples . Build a small yet highly productive team to support the vision and mission for proliferating practical machine learning and scalable computing techniques at Ford Motor Company Lead by example via training, consultancy and hands-on technical work Develop strategies for community learning and knowledge management in the related analytics domains Share and present work to cross-functional teams and execute leadership Develop strategies and best practices for leveraging Ford’s heterogeneous data sources and large-scale computing resources Master’s degree in a quantitative field such as Computer Science, Computer Engineering, Statistics, Economics, Mathematics, Physics 5+ years of experience with distributed computing, machine learning, or data processing 5+ years of experience with scalable solution design and development 5+ years of experience with consulting and professional services practices 5+ years of experience in at least two of the following languages: Java, Scala, Python, SQL, C/C++ Ph. D. in a quantitative field such as Computer Science, Computer Engineering, Statistics, Economics, Mathematics, Physics 2+ years of experience with Agile Software development 2+ years of experience with NoSQL tools such as Solr/Elastic 2+ years of experience with Functional Programming 2+ years of experience with environment configuration and software development on Linux based systems Scientific thinking and the ability to invent 150 Machine Learning / AI Architect, West Region Resume Examples & Samples . Minimum 3 years of experience utilizing statistics, data analytics, machine learning, or natural language processing Minimum 5 years of experience in developing innovative approaches and new algorithms to solve difficult business problems Minimum 1 year familiarity with general AI capabilities, including virtual agents, robotic process automation, and video analytics, among others Experience distilling and presenting complex concepts to a business audience. Experience with IBM Watson AI capabilities Proven ability to work creatively and analytically in a problem-solving environment Critical thinking skills to assess how AI capabilities can best be applied to complex business situations Excellent communication (written and oral) and interpersonal skills 151 Head-artificial Intelligence & Machine Learning Resume Examples & Samples . Stay ahead of the curve on AI, develop a point of view, publish in peer reviewed journals and file patents Solve real world client relevant business problems Hire, motivate, and develop data scientists A Ph.D. in Computer Science, with focus on Artificial Intelligence, Machine Learning, Deep Learning, or Natural Language Processing (or highly experienced B.Tech, M.Tech and M.Sc graduates from top programs in CS, EE, Statistics, Econometrics, Math, Physics) Expertise in applying artificial intelligence methodologies to real world business problems Experience in general purpose programming language like Python or C Strong problem-solving skills and ability to think creatively Ability to work in unstructured and ambiguous environment 152 Machine Learning Performance Intern Resume Examples & Samples . Candidates must be pursuing a master's level or a PhD level degree in a technical discipline Experience implementing machine learning algorithms Knowledge of C++ 153 Machine Learning & AI Developer Resume Examples & Samples . Analyzes, designs, programs, debugs, and modifies software enhancements and/or new products used in local, networked, or other programs Code may be used in commercial or end-user applications, such as materials management, financial management, HRIS, or desktop applications products Using current programming language and technologies, writes code, completes programming, performs testing, and debugging of applications Completes documentation and procedures for installation and maintenance Collaborates with technical and non-technical associates to understand user and organizational needs specific to at least one system process or component on projects within manager’s domain Completes coding using proper coding and quality standards May interact with users to define system requirements and/or necessary modifications Good knowledge in the following areas: o Technical knowledge in software development methodologies 154 Machine Learning Software Dev Engineer Resume Examples & Samples . BS in Computer Science or related field with 1+ years of relevant work experience Strong object-oriented design and coding skills (Java, Python, and/or C++) preferably on a Unix or Linux platform Deep understanding of data structures, algorithms and distributed systems You have implemented distributed algorithms that operate on one or more GPUs, preferably using the CUDA platform You have a solid understanding of matrix and vector mathematics. You have experience developing software that uses linear algebra libraries such as BLAS and LAPACK Experience deploying applications within software containers You're familiar with AWS technologies from a customer perspective 155 Machine Learning Resume Examples & Samples . Analyze source data and data flows, working with structured and unstructured data Manipulate high-volume, high-dimensionality data from varying sources to highlight patterns, anomalies, relationships and trends Apply AI/Machine Learning technology to solve real-world problems Analyze and visualize diverse sources of data, interpret results in the business context and report results clearly and concisely Execute both descriptive and inferential ad hoc requests in a timely manner Communicate and present models to business customers and executive Work collaboratively with different business partners and be able to present result in a clear and concise manner Teach and mentor others in the use of AI/Machine Learning Bachelor’s degree in a field such as Computer Science, Computer Engineering, Statistics, Economics, Mathematics, Physics 2+ years of experience of functional programming with Python, Scala or LISP 2+ years of experience with SQL, Spark, Hadoop 2+ years of experience with Machine Learning and Artificial Intelligence techniques and tools such as neural networks, regression, classification and clustering 2+ years of experience with data sources and platforms (Unix/Linux, Teradata, Hadoop, Oracle, SQL Server and DB2) Master's Degree or PhD in a quantitative field such as Computer Science, Computer Engineering, Statistics, Economics, Mathematics, Physics Demonstrated ability in the application of Machine Learning/AI in real-world industrial settings with large scale data Experience with Deep Learning tools such as TensorFlow and Caffe on NVidia DevBoxes Experience with Agile software development Experience with parallel/grid computing is a plus Experience with contributing to open source projects is a plus Strong oral and written skills 156 Machine Learning Resume Examples & Samples . Contribute to evolving the technical direction of Ad Quality Systems and play a critical role their design and development Build and support billing pipeline responsible for handling all revenue impacting events in Sponsored Ads in real-time You will research, design and code, troubleshoot and support. What you create is also what you own Develop the next generation of automation tools for monitoring and measuring Ad Quality, with associated user interfaces Have the satisfaction of seeing your work impact hundreds of millions of Amazon customers and thousands of Amazon merchants in several countries Be able to broaden your technical skills and work in an environment that thrives on creativity, efficient execution, and product innovation Bachelors (BS/BE) in Computer Science or related field 3+ years of experience in software development and full product life-cycles Top notch coding skills in Java and/or C++ coupled with strong base in object-oriented design and SOA Strong proven ability in building high-performance, highly-available and scalable distributed systems Demonstrated experience in SQL and data modeling skills Proficiency with at least one of these scripting languages: Perl / Python / Ruby / shell script Strong sense of ownership and drive Sharp problem solving skills and ability to resolve ambiguous requirements Strong knowledge of data structures, algorithms, and designing for performance, scalability, and availability Ability to learn new technologies and systems Advanced Degree (MS/ME/PhD) in computer science or related discipline or 4+ years of relevant industry experience Expertise in Map/Reduce systems such as Hadoop / Hive / Flume Experience in Machine learning or web crawling Knowledge of HTTP Protocol, REST, XML, J2EE, JavaScript, AJAX a plus Familiarity with Pay for performance Ad model and the Internet advertisement industry is a plus Experience with Amazon Web Services is a plus 157 Image Processing & Machine Learning Intern Resume Examples & Samples . Image processing and computer vision Machine learning Deep learning Mathematical background Python and C++ Experience with TensorFlow and/or other deep learning libraries Ability to iterate quickly and think outside the box Experience with shaders An artistic touch ;) 158 Machine Learning Expert for Speech Research Resume Examples & Samples . PhD in Electrical Engineering/Computer Science or related fields. Outstanding M.Sc. candidates can also apply Academic background in relevant areas, in particular machine learning. Previous experience related to speech and additional background in deep learning is an advantage Industry experience and strong programming skills in C++, Matlab are an advantage 159 Private Machine Learning Server Engineer Resume Examples & Samples . 3+ years practical background in server software engineering and distributed systems Proven track record delivering production software Deep fluency in Java, C++, or another production language Experience with Spark, Hadoop, MPI, or other distributed frameworks Solid mathematical knowledge; understanding of machine learning or statistical inference a plus Strong initiative and independence 160 Machine Learning Software Engineer Resume Examples & Samples . MS or PhD in Computer Science, Electrical Engineering or a quantitative field Ability to partition algorithms across highly parallel computing platforms, and to analyze and benchmark performance of the resulting implementation is core to this position Implementation of complex signal processing on at least one of the following platforms: FPGAs, ASIC, ASSP, GPP, GPU, DSP Familiarity with techniques for optimizing CNNs to minimize off-chip memory bandwidth requirements, storage requirements and to minimize compute requirements Experience with programming languages including but not limited to C/C++ and Python Experience with Tensor Flow, Caffe, Theano or other similar frameworks would be an advantage Experience with machine learning algorithms, deep convolutional networks (DCNN), recurrent and other networks is advantageous for this position Knowledge of network training algorithms and state-of-the-art techniques for CNN weight compression, quantization, binary networks, and pruning strategies are highly desirable Implementation experience of DCCN in software and/or hardware (ASIC); realization of these algorithms is highly valuable DSP processor design experience would also be looked upon favorably 161 Machine Learning Product Manager Resume Examples & Samples . B.S / B.A degree with a strong academic record 3+ years working in Product Management, including multiple years in a STEM field Experience writing detailed product requirements Bilingual in tech and layperson, and able to collaborate with cross-functional teams Experience working in Agile/Scrum environments A/B testing and metrics analysis 162 Machine Learning Intern Resume Examples & Samples . Currently pursuing a Masters or PhD in Computer Science, Mathematics, Statistics, or Physics (Machine Learning or Deep Learning is a plus) Proven programming skills such as SAS, Python, Lua, R, C, or C++ Experience with ML libraries such as scikit-learn or DL frameworks such as TensorFlow Able to work 15-20 hours a week during the school year in the Cary, NC Office (Must be attending a school local to that area) Not graduating prior to May 2017 163 Machine Learning Expert Resume Examples & Samples . Explore, understand, and implement most recent algorithms and approaches for supervised and unsupervised machine learning Understand business processes which create and consume data so as to be able to select best approaches, evaluate their performance and asses business relevance Create excellence both in terms of results quality and system scalability through continuous evaluation, analysis and refinement of the system implementation Master degree in Computer Science, Mathematics, Statistics, Operations Research or related field Track record of developing novel learning algorithms and/or systems Experience with Machine / Deep Learning software packages such as TensorFlow/MXNet/SparkML 164 DBS APJ SII Lead-iot & Machine Learning Resume Examples & Samples . Relevant professional degree, as well as adequate career in the industry Profound knowledge of the SAP Services business for the respective area & internal processes Proven leadership of organizations, teams and individuals Very strong analytical, and conceptual skills Pro-active driver, team-player, results-oriented, with a can-do attitude Strong business and commercial acumen Works, collaborates and influences key stakeholders across organizational layers Excellent communication and presentation skills in English Overall management responsibility of the APJ l IoT business (end-state: 25 digital references by end 2017, helping win the deals, helping GCD plan the work force in every MU, working with License) covering the entire DBS-portfolio with strong leadership in operational management/-excellence as well Accountable for business planning Drive the adequate Service- / Delivery- / Skill-Mix for efficient and successful delivery to customers Collaborate with Universities, Research Institutes, other companies regarding all elements of Machine Learning & IoT Decision making and de-escalation in critical cases Active support of customer engagements in executive sponsor roles in collaboration with Minimum 10-12 years in services delivery At least 8 years as a manager 2-3 Years of Experience in ML / IoT-related areas 165 Program Consultant for Machine Learning Resume Examples & Samples . 1) Experience with program and delivery management 2) Having a network throughout SAP to successfully go through the SAP Cloud Cycle 3) Ability to work in an innovative environment facing so far unknown challenges 4) Guide agile development teams through SAP standard software development processes and SAP Cloud Cycle Support the program in the execution of the product definition and delivery process, including expectation, risk and change management Coordinate and track the standard software development lifecycle tasks and product standards in Sirius in order to ensure Machine Learning product delivery in time, quality, and scope Guide project/product teams through SAP Cloud Cycle processes and ensure compliance Represent the Machine Learning program in the release planning of the SAP products which integrate Machine Learning application as extension (i.e. S/4HANA, SuccessFactors, Concur, Ariba, etc) Drive cross unit alignment regarding Machine Learning products and services and cross program administration tasks Prepare and provide management reporting on program and product level, perform monitoring of critical topics and activities Understand the machine learning products to bring to the market to provide the best possible go-to-market consulting Pick-up other varying Machine Learning cross tasks over time Degree in Computer Science, Information Systems, Business administration or related field Track record of SAP program and project management experience Knowledge of the SAP Cloud Cycle, Corporate Standards and Shipment Channels Knowledge of JIRA and Sirius Ability to handle exceptions and manage escalations and excellent analytical skills Network within SAP to tackle all portfolio relevant issues paired with good stakeholder management and negotiation skills Excellent verbal and written communication skills in English language. German is an advantage 166 Software Engineer, Machine Learning Resume Examples & Samples . Explore Machine Learning open source/commercial solutions with focus on neural MT Develop prototypes and validate the results Contribute to the production solutions’ development, testing and deployment Document and communicate the intent and the results in clear terms to both technical and non-technical team members Keep current with latest trends and technologies to anticipate future development needs and requirements Collaborate closely with various groups throughout the company and across multiple geographic locations to deliver outstanding solutions and offerings Team player, yet responsible for owning deliveries BS/MS in Computer Science with a background in Machine Learning, Artificial Intelligence or related technical field Hands-on experience in Machine Learning, Artificial Intelligence and data analytics techniques Knowledge of one or more open-source Machine Learning framework Good hands-on experience in one or more of the following languages: Python, Java, Scala Familiar with Linux/Mac environment Ability to quickly adapt to new situations and to learn new technologies Ability to collaborate and communicate effectively with a multicultural local and remote team Excellent written and oral communication skills in English Experience with machine translation Hands-on experience in Object-Oriented design and programming Familiar with Agile development practices, Continuous Integration, collaborative development environments and version control systems such as git 167 Software Development Engineer Alexa Machine Learning Platform Resume Examples & Samples . Proficiency in data structures, algorithm design, problem solving, and complexity analysis Development experience in a Unix/Linux environment Experience designing, building, deploying, operating, scaling, and evolving distributed systems Mastery of a variety of modern programming languages (Java, JavaScript, C/C++, Objective C, Python, Ruby) and open-source technologies (Linux, SQLite, OpenGL, Spring, Hadoop, Spark, Mesos, Rails) Strong sense of ownership, urgency and drive Demonstrated leadership abilities in an engineering environment in driving operational excellence and best practices Demonstrated ability to achieve stretch goals in a highly innovative and fast paced environment 168 Head of Machine Learning Resume Examples & Samples . Ensuring that the measurement practice leverages state of the art technology in machine learning to measure effectiveness of advertising Develop and deploy library of decision making and machine learning algorithms for advertising measurement Build econometric models required to retrospectively measure the financial impact of mass advertising spend, and inform volume and mix of future spend Calibrate models through carefully designed experiments Objectively raise the bar on applications of machine learning for advertising measurement and optimization 10+ years work experience including a combination of building scalable software systems and managing machine learning infrastructure or PhD with 8+ years of work experience. At least 5 years in software development industry Experience with big data technologies Experience using one of R, MATLAB (or similar tools) is required Experience developing production code in C++/Java Experience using optimization algorithms for decision making Bachelor’s degree or equivalent professional experience Experience with consumer-level data analyses Experience with mass advertising datasets Consumer Electronics experience, both US and international Experience handling large datasets Candidates with a Ph.D. in a relevant field are preferred Master’s degree in engineering, computer science or a similar quantitative field 169 Principal, Machine Learning Resume Examples & Samples . Develop prototypes by manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources Work closely with Business, Product and Technology teams to model real-time experiments, implementations and new feature creations Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Research and implement novel machine learning and statistical approaches Counsel/Advise partners/users on data capabilities and potential short-comings Proficiency in Machine Learning related technologies (Python, Spark MLib, Spark/SparkR, Hadoop, etc.) Ability to partner with executives, business stakeholders and product managers to define roadmaps and to translate business needs into machine learning solutions Deep and applied experience leveraging data science and machine learning to solve business need Use machine learning, deep learning, reinforcement learning, statistical techniques to create scalable solutions Experience with algorithm development, data processing, statistical analysis and validation Proven track record of overseeing multiple data science and machine learning initiatives from idea generation to objectives formulation to implementation and deliverables Excellent communication and persuasion skills Bachelor's with significant experience, but preferably a Master’s degree, Computer Science or a related quantitative field Advanced degree in CS Machine Learning, Statistics, or in a highly quantitative field 8+ years of hands-on experience in machine learning and large data analysis 10+ years of experience using Python, R, Java in both a Linux/UNIX environment Strong programming skills in object oriented programming language (Java, Scala, Python, R, etc.) Experience in implementing the models that handle terabytes of data Proven record of applying Advance Analytics/Machine Learning to advance company initiatives Proven record of delivering results Strong communication and data presentation skills 170 Principal Engineer, Machine Learning Resume Examples & Samples . Using state of the art machine learning tools, design/develop advanced algorithms for enhancing the performance of audio transducers Using emerging machine learning tools, design/develop algorithms that will match and exceed human capabilities in speech recognition, detection and classification Evaluate and develop new audio applications for areas such as: virtual reality (VR), 3D-audio playback and recording, multi microphone and multi speaker arrays for localization and beam-forming, voice control interfaces and AI Design real-time audio applications and demos using real-time DSPs, Matlab tools, and Virtual Studio Technology (VST) applications Develop and integrate audio DSP algorithms and technologies for the professional audio, consumer and mobile environments Create IP for systems and technologies Technology scouting, to find and evaluate emerging technologies Conduct feasibility studies. Present technology demonstrations Collaborate with peers inside and external to HARMAN, both in the local office and in facilities globally Manage projects and technical resources, including planning, estimating and follow through using agile management PhD degree in Engineering or related field and 4 years of experience in corporate or academic research; alternatively, Master’s Degree in above mentioned fields and 8 years of experience in research and development or Bachelor’s Degree and 12 years’ experience 4+ or more years of experience in the audio and/or DSP related field Good working knowledge of machine learning concepts- data training methods, network generalization methods, neural network architectures for machine learning Experienced with C language programming for DSP applications Experience in digital signal processing, in particular speech and audio processing Good working knowledge of MATLAB Experience in developing proof of concept strategies Experienced working within an agile development framework Exemplary verbal and written communication skills Creative problem-solver capable of creating new techniques, technologies and methods Capable project management and time management skills Expertise in machine learning areas, in particular acoustic/speech applications Expertise in speech and audio processing areas, in particular, speech enhancement and noise mitigation Passion for audio and music 171 Computer Vision & Machine Learning R&D Engineer Resume Examples & Samples . Strong machine learning background, with hands-on experience in building real systems Strong background in mathematics and/or statistics is highly desirable Demonstrated ability in both research and development Experience integrating machine learning algorithms into applications Strong C and C++ coding skills Strong command-line proficiency (posix tools, scripting, git) Experience in signal processing, computer vision, and other related applied engineering fields a plus Proficiency and experience in these languages are highly desirable: Python, Matlab, Objective-C, Swift, GPGPU (Cuda/OpenCL/Metal) OS X and/or iOS development experience a plus Ability to work hands-on in cross-functional teams with a strong sense of self-direction 172 Technical Sourcer, Machine Learning Resume Examples & Samples . 3+ years technical sourcing experience with a search firm or in-house recruiting team 1+ years software engineering recruiting experience Research/sourcing skills with ability to dive into searches to fill requisitions A candidate engagement approach with ability to activate passive candidates Interview skills with ability to screen for both technical and cultural qualities Tech and industry knowledge with ability to understand relevant tech skills, target companies, conferences, open source communities 173 Postdoctoral Researcher Machine Learning Based Cardiology Fixed Term Resume Examples & Samples . Ph.D. in Mechanical or Electrical Engineering Track record of research publications in high-quality journals and conferences Proven ability to collaborate in research teams Ability to work with and maintain close connections with other teams around the world 174 Pe-big Data / Machine Learning Resume Examples & Samples . 8 to 10 yrs of experience including 4 to 5 yrs on hadoop, machine learning,cloud and NoSql areas Demonstrable excellence in innovation, problem solving, analytical skills, data structures and design patterns Experience in refactoring and re-engineering of enterprise systems and good understanding of functional aspects Extensive experience with Hadoop and Machine learning algorithms Extensive experience working with Oracle, SQL, PL/SQL and Data Warehousing Strong programming skills in Java/Python and Linux 175 Senior Product Manager Machine Learning & Time Series Resume Examples & Samples . Work with various product development and design teams to formulate our product vision, strategy, product roadmap, define new experiences, and enhance existing functionality Defining and prioritizing a backlog of work including the creation of stories for new features and enhancements to existing functionality, and improving product quality by tracking the rate of defects Work with global 2000 customers, some of the best brand names in the world, to determine needs, unmet needs, business goals, product usage, and refine ideas with concepts and product feedback Be the voice of the customer, providing customer and business value perspective during day-to-day conversations with development Coordinate across multiple stakeholders (engineering, marketing, customers and partners) to understand needs, manage expectations and feature tradeoff decisions Collaborate with Product Marketing to produce product overview, licensing, and other go-to-market materials Maintain a firm grasp of the competitive landscape and identify areas of competitive differentiation for internal consumption and competitive programs Work with User Learning (Help files and documentation), Training, and Support and Professional Services to assure smooth uptake and adoption 5+ years of experience as a Product Manager, Product Owner, Consultant or technical Product Analyst in a commercial software product company 3+ years of experience with reporting, analytics, business intelligence, and big data The ability to learn new technical concepts quickly The ability to make trade-off decisions between possible and desirable, which requires a good sense of what is technically feasible The ability to context switch between future product planning and current product adoption activities The discipline to focus on high leverage activities. This means you must be good at saying 'no' and having people be ok with it, which means you must be good at articulating how your high leverage work will benefit them Passion about our products and the possibilities the come from building a world class ecosystem of customers and partners The ability to generate ideas for how our products can make our customers more successful Must enjoy working in a highly collaborative environment Comfortable delivering product presentations to large audiences 176 Data Trend Analysis With Machine Learning Algorithms Resume Examples & Samples . Responsible for creating and demonstrating a proof-of-concept for Business stakeholders Responsible for delivering the information standard to the Business Owner and developing a robust maintenance process for the solution Responsible for ensuring alignment of the information solution with existing IT and Enterprise Architecture strategies Six sigma data analysis capability, trend analysis An ability to decompose business strategies to the information layer The capability to communicate with Business stakeholders in their terms Capability to rapidly understand the current business technology landscape in order to hold credible discussions with the business and effectively represent IM Solid experience in understanding at least 2 different business teams (Engineering, Manufacturing, Purchasing etc.) and their information needs Demonstrated proficiency with VBA, VB6.0, .Net, Java, PL-SQL, MS-Access/SQL-Server/Oracle database, Machine Learning algorithms and at least one scripting language (ASP.Net, JavaScript) Hands on experience coding for Microsoft and Java technologies with RDBMS and its ecosystem technologies Leadership skills to supervise and lead Information Management projects Ability to develop executive level support for expected benefits from IM technology Post-graduate degree in Engineering / Manufacturing Systems / Systems Theory, Business Administration, or academic equivalent Proven business value analytics capability to robustly examine large data sets and highlight patterns, anomalies, relationships and trends Demonstrated experience and expertise in conceptual thinking of how to apply information solutions to a business challenge Excel analysis and visual basic macro development Ability to manage deliverables according to a robust project plan Evidence of being able to transfer technology to business stakeholders Technical advisor to peers and colleagues within the function Demonstrated leadership and teamwork Backfill candidate has already been identified Computer Science or related 177 Machine Learning Researcher Resume Examples & Samples . Develop the team’s capabilities in data science and machine-learning, and apply them to create new data-driven insights Create innovative, systematic investment signals and strategies based on a rigorous, peer-reviewed research process Work with every investment team in MBFI (Credit, Macro, Equities, RV, Securitized, Mid-horizon etc.) to introduce cutting-edge techniques and innovative data sources across the Fund Contribute to broader research initiatives across BlackRock 0-3 years’ experience in quantitative analysis or similar role Practical experience of working with large and complex datasets – preferably but not necessarily in a finance context. An enthusiasm for exploring, analyzing and enhancing data Practical experience of applying statistical/machine learning methods – again preferably but not necessarily in a finance context Formal training in a numerate discipline such as Mathematics, Statistics, Quantitative finance, Statistics, Economics/Econometrics etc, to at least Masters level Very strong experience in quantitative programming/research: Python preferred (MATLAB and R knowledge also helpful Strong experience in working with databases and related tools 178 Machine Learning Expert Cto Module Lead Blr Resume Examples & Samples . 2+ years of experience in application of Machine Learning or adjacent areas such as computer vision, natural language processing for text mining etc Exposure in both the theory and practice of machine learning techniques (supervised and unsupervised learning, Artificial Neural Networks, Belief networks etc.) Prior experience with a (m)any of the following models: Logistic Regression, Linear Regression, Support Vector Machines, Multi-level/Deep Neural Networks , Hidden Markov Models, Conditional Random Fields, Random Forests, Time series Models, Social Network models Ability to decide, articulate what machine learning algorithms / techniques would be most suitable for a given problem scenario Programming expertise in Python (Mandatory) Good to have programming languages exp in (C++, R and Matlab / Octave) in UNIX/Linux environments High self-motivation, focus and enthusiasm to gather & prepare data to the required format for ML models and validate Experience working in any or more of industry verticals like Retail, Consumer Products, BFSI, Travel and Logistics High integrity Strong analytical and problem-solving skills, along with the creativity to work around road blocks Ability to articulate strategy & direction effectively in a team environment Learning Attitude and team player As a individual contributor you will be responsible for building models to derive insights from large amounts of diverse data Gather, process and analyze large dynamic real-world data sources Define reusable components/frameworks, standards to be used & tools to be used and help bootstrap the engineering team Identify areas, conceptualize, prototype and prove benefits in turning ideas into machine learning models in the domain of Mindtree customers Transfer knowledge gathered through Proof of Concept solutions to full solution implementation team Develop new and customer relevant machine learning techniques / models. Map state-of-the-art Machine Learning algorithms to customer use cases Assess and compare 3rd party machine learning tools and platforms Help PM in identifying key technical risks and mitigation plan for the same Help PM in effort estimation and planning Interface with academia Write ‘Point of View’ document on emerging trends in ML / AI Conduct internal sessions on related topics 179 Machine Learning & Computational Engineering Researcher Resume Examples & Samples . Search out new opportunities within ARM to apply ML and other emerging computational techniques to the engineering process. This includes interacting with hardware engineers and others across ARM to understand their existing techniques and their most pressing problems Keep abreast of the current state of the art in ML, and apply those existing techniques to the problems we identify Find areas where existing ML techniques are unsuitable for ARM’s problems, and devise new techniques which excel in those areas. For example, many existing ML techniques rely on the differentiability or local connectivity of the problem domain, but these properties often don’t hold true for hardware engineering problems Roll out the results of your research across ARM and the ARM ecosystem to make our engineering process more efficient, productive, and profitable Publish the results of your research to contribute to the overall progress of our field A Ph.D. in electrical engineering, computer engineering, computer science, or other relevant field Classroom, research, and/or work experience in machine learning Good knowledge of computer architecture Strong programming skills 180 Machine Learning Software Engineer Resume Examples & Samples . A Masters’ degree with several years’ experience or a PhD in software engineering or related field In depth experience with Spark/Hadoop and either Theano/Tensorflow/Caffe/Torch Experience in Python and R Experience creating production environment data analytics and applications 181 Machine Learning Internship Resume Examples & Samples . One year completion into a Master’s degree or PhD with a focus in machine learning or distributed computing An in-depth understanding of machine learning algorithms and modelling Experience with Spark/Hadoop and either Theano/Tensorflow/Caffe/Torch Experience in Python 182 Analytics Machine Learning Intern Resume Examples & Samples . Experience on developing production level code on one or more of the following areas- statistical modeling, machine learning algorithms, data pipelines Experience in data science projects, especially experience in scala, R and python Experience in communicating complex scientific results to a general audience using visualization tools Excellent at prototyping simple machine learning pipelines to quickly decide if an idea is promising or not, all the way from getting the data to measure model’s accuracy At-least 1 year experience on developing production level code on one or more of the following areas: statistical modeling, machine learning algorithms, data pipelines At-least 1 year experience in communicating complex scientific results to a general audience using visualization tools At-least 1 year experience in building production level machine learning pipelines using open-source technologies (hadoop, spark, hive, kafka, storm) At-least 1 year experience with deep learning frameworks such as Caffe, Torch, Theano or TensorFlow 183 Director of Machine Learning Resume Examples & Samples . Design and propose space and time efficient neural network architectures for mobile platforms Analyze, evaluate and assist in the design of mobile neural network silicon Lead and grow a team of machine learning experts; evangelize machine learning across other teams and disciplines in the company Passionate about innovation and discovery Minimum BS degree in Computer Engineering or Computer Science Minimum of 5 years experience in the field of ML and AI PhD preferred or equivalent expertise in ML and AI 10+ years experience in the field of ML and AI Nuanced understanding of all phases of machine-learning development 184 Software Development Manager Alexa Machine Learning Platform Resume Examples & Samples . Bachelor's Degree in Computer Science (MS, Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, etc.) Experience with the tools of the trade, including familiarity with modern programming languages (Java, JavaScript, C/C++, Objective C) and open-source technologies (Apache, Hadoop) Demonstrated track record of project delivery for large, cross-functional projects Experience presenting technical information to a variety of audiences both verbally and in writing The key requirement for this position is established skill designing and developing solutions to complex problems in a distributed systems environment Technical credentials, with at least 8 years experience managing software development teams, ideally with some hands-on architectural or distributed systems experience MS, Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, etc Experience with big data solutions Knowledge of ML fundamentals 185 Software Development Engineer Alexa Machine Learning Platform Resume Examples & Samples . Graduate degree (MS or PhD) in Electrical Engineering, Computer Science, or Mathematics with specialization in machine learning, natural language processing, or speech recognition Programming experience in C/C++, Java, or Python Experience in planning and learning techniques mainly reinforcement learning and dynamic programming Solid machine learning background and familiarity with state-of-the-art techniques such as deep neural networks Related work in creating dialog system Contributions such as publications that have advanced the field Solid software development experience Good written and spoken communication skills 186 Research Intern, Machine Learning Resume Examples & Samples . Develop highly scalable classifiers and tools leveraging machine learning, regression, and rules-based models Suggest, collect and synthesize requirements and create effective feature roadmap Perform specific responsibilities which vary by team Pursuing PhD in Computer Science, related STEM or quantitative field or relevant experience Must be currently enrolled in a full time degree program and returning to the program after the completion of the internship Experience in C/C++, Java, Perl, or PHP Experience in scripting languages such as Perl, PHP, Python, and shell scripts Experience with Hadoop/Hbase/Pig or Mapreduce/Sawzall/Bigtable is a plus Excellent interpersonal skills, cross-group and cross-culture collaboration Proven track record of achieving significant results Preferred: Demonstrated software engineer experience via an internship, work experience, coding competitions, or PhD papers 187 Performance Engineer, Machine Learning Resume Examples & Samples . Expert knowledge of C, C++, or Objective-C and the ability to write elegant, performant code Highly professional and collaborative with outstanding communication and presentation skills Experience with significant software projects where performance was imperative 188 Senior System Design Engineer Machine Learning & Artificial Intelligence Resume Examples & Samples . Vehicle Network Systems Wireless communication Artificial Intelligence (AI) and Machine Learning technologies useful for commercial transportation solutions High competence in communication and networking Composing technical and research results reports and documentation Presenting technical result Interacting with stakeholders at different levels Fluent in English, spoken and written 189 Technical Director Site Reliability & Machine Learning Engineering Resume Examples & Samples . Technical leadership of Level 2 Operations for WDAT including all major technology areas 10+ years of relevant experience in Technology Engineering or Delivery Experience in Site Reliability Engineering (Machine Learning) Demonstrated technical ability in core technology areas: Java, nodeJS, Angular, PHP, .NET, SQL, Oracle Demonstrable knowledge of TCP/IP, HTTP, application integration, monitoring, servers, storage & databases Ability to troubleshoot application and system issues at all levels of the stack Demonstrated expertise in leading triage & integration functions on enterprise-scale solutions Demonstrated delivery & solutioning on large-scale distributed systems including multi-tiered architecture Demonstrated experience in delivering results in a multi-sourced vendor environment, with delivery partners on & off-shore Ability to communicate to executive audiences, and deliver results through influence Technology experience in the hospitality/travel industry Masters in Computer Science, or related engineering discipline Demonstrated experience supporting solutions in International regions Certification in ITIL 190 Principal Engineer, Machine Learning Resume Examples & Samples . Design, implement, and deploy full-stack solutions for millions of Comcast customers Develop and prototype new algorithms, evaluate with small scale experiments, and later productionize solutions at scale Investigate and solve exciting and difficult challenges in machine learning, classification, data science, content analysis, and deep learning Collaborate witha cross functional agile team of software engineers, data engineers, ML experts, and others to address challenges head on Help drive optimization, testing and tooling to improve data quality Bring your experience implementing machine learning systems at scale in Java, Scala, Python or similar (not just R or Matlab) Care aboutagile software processes, data-driven development, reliability, and responsible experimentation Computer Science, Engineering Generally requires 11+ years related experience Publications at top-tier peer-reviewed conferences or journals or a proven track record of industry innovation in creating novel algorithms and advancing the state of the art Strong mathematics, statistics, and data analytics abilities Track record of successful projects in algorithm design and product development Experience developing / implementing anomaly detection or self-healing solutions Experience with data processing and storage frameworks like Hadoop, Scala, Spark, Storm, Cassandra, Kafka, etc 191 Software Development Manager Alexa Machine Learning Platform Resume Examples & Samples . Responsible for the over-all software development life cycle Management and execution against project plans and delivery commitments; Manage the day-to-day activities of the engineering team within an Agile/Scrum environment Work closely with our scientists and engineers to architect and develop the best technical design and approach Report on status of development, quality, operations, and system performance to management Customer engagement and product road map definition BS/MS/PhD in Computer Science or equivalent 5+ years experience building scalable parallel and distributed computing systems 2+ years experience directly managing software engineers Experience with object oriented programming languages Demonstrated track record of project delivery for technically complex, cross-functional projects Advanced degree in Computer Science, Computer Engineering, Electrical Engineering, etc Prior work experience in deep learning, numerical algorithms, parallel computing, heterogeneous architectures, scientific computing Experience with big data solutions such as Mesos, Spark, Hadoop DevOps experience 192 Machine Learning Project Manager Resume Examples & Samples . Desired Skills/Experience Aptitude for grasping new technical concepts involving application and tool development Knowledge of Linux IOS and/or Mac OS X experience Technical Degree in EE, ME or related field preferred Experience developing and releasing a consumer product Ability to filter and distill relevant information for the right audience Demonstrated experience managing multiple projects in a matrixed environment Ability to work in an ambiguous and always fast-paced environment is required Demonstrated ability to deliver large scale projects on-time with consistently successful results Excellent leadership skills with the ability to win the confidence of highly skilled developers Fluent in software engineering processes with considerable software release experience Understands and deals well with rapid development cycles; remains flexible and calm in the face of uncertainty BS/MS in Computer Science, Machine Learning, Statistics or other quantitative disciplines, or equivalent work experience 193 Machine Learning Validator Resume Examples & Samples . Understand the basic building blocks of Machine and Deep Learning stack and develop Integration tests to test the various workflows, for various segments based on requirements and use cases Profile the software stack ,develop and run Performance tests Assess the bottlenecks and help identify areas for optimization in close collaboration with developers Bring a customer perspective to the validation activities and be the customer advocate for usability, setup, etc Min of 3 years programming experience in C++ and Python scripting Understand fundamental Machine learning/ deep learning / neural networks/image processing concepts and use-cases Experience developing integration and system tests 194 Machine Learning Validation Engineer Resume Examples & Samples . Looking for dedicated validation resources in an Agile environment to continuously develop integration testing for new features and bug fixes Setup and maintain a ‘Continuous Integration’ model to feed the integration tests into the code integration process and debug/resolve integration issues Min. 2 years with B.S. or 1 year with M.S. in Computer Science or related field Experience with frameworks i.e. Caffe, TensorFlow or other frameworks 195 Machine Learning Intern Resume Examples & Samples . Must be pursuing a bachelor's degree in Computer Engineering, Engineering Science, Computer Science, Math or equivalent (please review) 3 months experience with C and C++ 3 months experience in using testing infrastructure and scripting environments such as Perl and Python 3 months experience in developing software in Linux and Windows.Verilog and VHDL an asset but not required 3 months experience with debugging tools such as MSDev Studio and GDB 196 Senior Engineer, Machine Learning Resume Examples & Samples . Bachelors + 5 yrs professional experience, Masters + 3 yrs professional experience or PhD in machine learning or adjacent fields (computer science, statistics, data mining, data science, big data, etc.) Expert knowledge in deep learning and are familiar with the relevant machine learning frameworks Knowledge of other recent machine learning algorithms (e.g. Bayesian Networks and Reinforcement Learning) as well as optimization techniques Proven ability to multitask and deliver on challenging software development tasks Excellent C++ programming expertise Experience with source code management, unit test, code review and issue tracking systems Knowledge of Linux and development on Linux systems Experience working independently in a large software setting Experience working with robot and/or automotive hardware Experience with simulation environments System integration and software architecture skills 197 Man GLG Machine Learning Research Engineer Resume Examples & Samples . Capturing, cleaning and analysing data to provide novel insights for the business Building tools that summarise and visualise data, to present findings to end-users Researching, designing and implementing machine learning algorithms that can be used to enhance the investment and trading process Providing machine learning and data science expertise to the organisation Working as part of a team to build data and machine learning driven applications and tools for the business, to improve profitability and risk management 198 Software Development Engineer Alexa Machine Learning Data Platform Resume Examples & Samples . Develop and maintain key system features Work in an Agile/Scrum environment to deliver high quality software against aggressive schedules 5+ years of industry experience Experience developing cloud software services and an understanding of design for scalability, performance, and reliability Development experience defining, developing, and maintaining REST based interfaces 199 Senior Software Development Engineer Alexa Machine Learning Resume Examples & Samples . Work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility Work with stakeholders to define and execute on the technical strategy for your team BS in Computer Science or equivalent 7+ years of industry experience Programming in one or more object-oriented languages like Java/Python/C#/Ruby/Objective C/C++ Experience building scalable infrastructure software or distributed systems Analytical abilities and proven design skills MS in Computer Science Mastery of the tools of the trade, including a variety of modern programming languages (Java, JavaScript, C/C++, Objective C, Python, Ruby, C) Experience developing cloud software services and an understanding of design for scalability, performance and reliability Development experience defining, developing and maintaining REST based interfaces 200 Software Engineer New Machine Learning Initiative Resume Examples & Samples . Proficiency in at least one modern programming language such as Java, C#, C++, C , or Ruby/Python/Perl Good communication skills in explaining technical challenges and solutions Success in dealing with ambiguous problems and thinking abstractly Expertise in Hadoop ecosystem (HDFS, MapReduce, Spark, HBase, Hive, Presto, etc.) Core competencies in Scala, Java, HTTP, and JSON Experience building and operating large distributed highly available services Proven track record on delivering results, especially in the area of writing high-performance, reliable and maintainable code Ability to work well in a team environment and effectively drive cross-team solutions that have complex dependencies and requirements Strong technical vision, presentation and technology leadership skills 201 Machine Learning Software Intern Resume Examples & Samples . Strong background in Python and/or Java. Prior experiences with math/machine learning libraries are required. Particularly, experience with deep learning libraries (Theano/Caffe/Torch/TensorFlow) is highly desired Development experience with Raspberry pie (or similar on Linux platform) and must have experience with Android Graduate level familiarity with machine learning and basic understanding of signal processing techniques. Prior experience with audio signals will be a plus Hands on experience in developing/testing research prototypes with real-time machine learning capabilities Degree Level: MS, PhD students in Electrical Engineering, Computer Science 202 Machine Learning Model Interpretability Resume Examples & Samples . Engineers and scientists at Bosch Data Mining Services, North America, work on a broad variety of problems, from analysis of manufacturing processes to economics-based sales forecasting. The internwill be expected to help build a tool to enhance the insights derived PhD/MS in Machine Learning or related quantitative field Excellent quantitative, empirical analysis and research skills Strong knowledge of machine learning models, tools, and techniques Proficiency in Python, R, or another programming language suitable for modeling and statistics Excellent knowledge of analytical tools including Python scikit-learn, R machine learning packages, or similar Familiarity with relational databases and SQL Previous experience in building human-interpretable models, “white box” or “gray box” modeling, or other explanatory methods 203 Speech Signal Processing & Machine Learning Intern Resume Examples & Samples . MS or PhD in Electrical Engineering, Computer Science, or related fields Strong background in signal processing, machine learning, pattern recognition, and recent speech technology Familiar with state-of-the-art algorithms such as i-vector, PLDA, HMM/GMM, DNN, etc Strong coding skills, with at least 3 years of programming 204 Machine Learning Engineering Intern Resume Examples & Samples . Analyze large sets of imperfect data with machine learning and statistical analysis to derive actionable outcomes based on specific business problems Work with operations to gather feedback and improve existing automation tools Write scripts for test automation 205 Machine Learning Lead Developer Resume Examples & Samples . Design and develop modules for the SaaS based platform as per requirement from Product Managers & Architects, comfortable in writing automation as part of the feature delivery Apply machine learning, deep learning and NLP algorithm to big data sets Responsible for meeting all module technical requirements and associated schedule milestones Work with team members to do requirements & dependency analysis & write design documents Effectively communicates with members of the technical staff and Product Managers & Architects to ensure successful production and integration of quality software Identifies and reports project risks to management and drives to resolution Work with customers to troubleshoot issues, participate in technical discussions with customer facing groups like support and consulting to provide guidance and expertise on the products and deployment Understand real world deployment and usage scenarios from customers and product managers and translate them to product features that drive value of the product Work with other internal groups like QA and technical writers through the development cycle Bachelor’s in Computer Science or equivalent, with 5+ years of experience in product development and analytics algorithm design and implementation Proficiency in server side development using Java, Python or Scala Strong mathematics, data analytics and statistics background Experience in multi-threaded programming (concurrent library), NIO, RESTEas is highly desirable Ability to automate testing for the modules developed is required Experience in developing a SaaS product is highly desirable Experience in Cloud Computing, Big Data technologies such as Spark, Storm, Hadoop, Cassandra or other NoSQL DBs, Elastic Search, Kafka, Docker is preferred Experience working in an agile development environment and tools is required Ability to quickly learn new languages and technologies as required for a successful project delivery LI-PM1 206 Software Engineer New Machine Learning Initiative Resume Examples & Samples . 4+ years development experience Proficiency in at least one modern programming language such as Scala, Java, C#, C++, C, Ruby, JS, or Python Excellent self-directed learner Entrepreneurial drive and passion for customer success Experience designing new systems for scale and flexibility from the ground up Broad understanding of modern cloud computing technologies and their tradeoffs History of leading successful web service creation and operations projects Masters degree or Ph.D. in Computer Science or an engineering discipline A strong track record of project delivery for large, cross-functional, projects Experience in SQL and noSQL databases Experience in both front end (e.g. HTML/JS/CSS) and backend technologies (Java, Node.js, Ruby on Rails, Cloud services) 207 Machine Learning Director, Special Projects Resume Examples & Samples . Bachelor’s Degree in Computer Science, computer engineering or related field 10+ years professional experience in software development Experience in Healthcare IT/Healthcare analytics Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis Strong proficiency Java and/or C++, Python Experience with Amazon machine learning tools such as EML, MxNet Experience building complex software systems that have been successfully delivered to customers Experience in building large scale distributed systems and familiarity with distributed frameworks like MPI, MapReduce, Spark Familiar with electronic medical records (EMR), clinical classification systems and standard (HL7, ICD, SNOMED, CPT) 208 Instructor, Machine Learning University Resume Examples & Samples . Teach foundational MLU 6-week modules: Teach five, 90-120 minute lectures and project or final exam for each module taught in a 6-week session, integrate practical ML skills in each lesson plan, and coordinate with other instructors to maintain consistency Develop and revise module curriculum: coordinate with Amazon scientists and program staff to enhance the practical relevance of module content and infuse current Amazon ML applications to the learning experience Work with MLU program staff to ensure that students continue receiving a high-quality, university level educational experience while remaining full time Amazon employees Coordinate with other MLU instructors and Teaching Assistants. Support the continuous engagement with Amazon scientists who contribute to the program as instructors and technical consultants Ph.D. or M.S. in computer science, machine learning, mathematics, or related field; research in machine learning Teaching experience in higher education as graduate teaching assistant, instructor, or faculty member Ability to teach foundational content in mathematics, linear and logistic regression, and basic data science Strong programming skills Experience teaching professionals, leveraging adult-learning teaching and motivation frameworks Experience developing and teaching blended learning opportunities for adults 209 Software Developer / Machine Learning Resume Examples & Samples . BS in computer science 5+ years experience in software development Mathematical ability Skills with Java, C++, or Python or other programming language, as well as with R, MATLAB, Python or similar scripting language Masters or PhD in computer science or related fields 10 years of relevant experience in industry and/or academia 3+ years of hands-on experience in predictive modeling and analysis 210 Solution Expert for the SAP Machine Learning Brand Resume Examples & Samples . Degree in Computer Science, Business administration or related field Knowledge of product development processes delivery from ideation to successful go-to-market Experience in marketing event coordination and field enablement are very welcome Track record of program and project management experience Strong customer focus and business acumen High quality focus and result driven personality Excellent abilities to manage internal and external stakeholders Excellent written and oral communication skills in English; German a plus More than 5 years of experience in relevant positions 211 Manager, Machine Learning Resume Examples & Samples . scijobs MS in CS focused on Machine Learning, Operations Research, Statistics or other relevant area 5+ years of experience in an industrial applied science setting, where your work was directly incorporated into production systems Expertise in R, SAS, MatLab or other statistical software Strong computer science fundamentals including data structures and algorithms Programming expertise in languages such as Java / Scala / Python / C++ Exceptional problem solving ability PhD in CS focused on Machine Learning, Operations Research, Statistics or other relevant area 7+ years of experience in an industrial applied science setting, where your work was directly incorporated into production systems 2+ years of experience personally writing production quality code 212 Machine Learning Researchers Resume Examples & Samples . Work closely with machine learning experts to design, implement, tune, and optimize machine learning algorithms Design and implement experiments to test the quality of machine learning algorithms Validate promising research concepts with high quality Python, Matlab, or Julia implementations Apply software engineering best practice: software design patterns, version control, unit tests, documentation Work with a diverse group of technical experts to incorporate their expertise into software projects PhD in computer science, statistics, applied mathematics, or physics Experience in statistical methods for machine learning, ideally including probabilistic models, with a focus on Boltzmann machines and MCMC techniques Demonstrated success in the application of machine learning to practical problems Expert coding abilities. Preference given to demonstrated experience using Python, Matlab, or Julia Self-motivated, proactive and flexible with excellent problem solving skills 213 Senior Software Engineer, Machine Learning Resume Examples & Samples . MS degree in Software Engineering or related field 8+ years of programming experience in Java, Scala, C++ or C# 5+ years of experience with large scale big-data processing or with large scale real-time applications 3+ years of experience with Hadoop and MapReduce 3+ years of experience implementing machine learning algorithms Passion for exceptionally high quality code, algorithms, creative problem solving, empowerment, agility, teamwork and superb communication Curiosity and drive - you love solving the hardest problems 214 Senior Machine Learning Algorithm Developer Engineer Resume Examples & Samples . 4+ years of school work or related experience developing original mathematical algorithms or quantitative analysis techniques 4+ years of experience with MATLAB or C/C++ Demonstrated mathematical problem solving ability and data analysis experience Demonstrated interpersonal communication, presentation skills, verbal and written communication skills Strong desire to learn, take initiative and contribute in a team-oriented environment Must have an active DoD Secret clearance U.S. Citizenship status is required as this position needs an active U.S. Security Clearance as of day one of employment Minimum 3+ years in developing advanced algorithms. In particular machine learning algorithms such as Hidden Markov Model, Markov Decision Processing, Partially Observable Markov Decision Processing, Deep learning, Neural network, clustering (k-means, G-means), Gaussian mixture models, Bayesian reasoning, Bayesian theory, information theory, Dempster-Shafer, Graph theory, etc Should be strong in Statistical signal processing, signal processing, probability theory, detection/estimation theory Programming language: Expertise in Matlab (including object oriented programming in Matlab); some knowledge in C, C++, Linux/Unix preferred Customer focus and collaboration skills Demonstrated team leadership experience An understanding of the physical limitations to implementing complex algorithms in real hardware 215 Dir, Machine Learning Resume Examples & Samples . Lead discussions around business objectives related to AI/ML across variety of commercial stakeholders, including executives Guide the direction of the Digital Office AI/ML offering and lead technology evaluations and selections Understand and educate decision-makers on latest industrial and academic developments in AI/ML Guide team to make innovative architecture and technology recommendations for the Digital Office AI/ML offering Lead team to develop new ideas and apply AI/ML offering to complex product challenges across Technology Solution Lead team to study and innovate in AI/ML and its application in the mobile domain Lead architecture review and approval processes for solution architectures Work with Digital Office team to conduct proofs of concept for emerging technologies and business concepts related to AI/ML Collect, synthesize, and propose requirements for the QuintilesIMS AI/ML offering Create and manage solution roadmap Oversee the end-to-end development and implementation of the AI/ML offering MS or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field 10+ years of software engineering and architecture experience Expert-level understanding of Artificial Intelligence technologies including: Machine learning; Computer Vision; Natural Language Processing; Deduction/reasoning Solid knowledge in deep learning algorithms and the latest architecture for AI Experience in a technical leadership or management role but also willing to get hands into code Have an overwhelming passion for learning new technologies and building new things Demonstrate strong written, oral, interpersonal communications skills and can engage at all levels including executive 216 Head of Machine Learning Resume Examples & Samples . 5+ years of experience in a Machine Learning role utilizing natural language processing and data mining PhD in Computer Science Functioning high level understanding of Finance Experience working with and managing large data sets Exceptional programming skills in Python, Matlab, and Hadoop 217 Consulting Engineer, Machine Learning & AI Resume Examples & Samples . 8-10 years of experience Background in deep learning and convolutional neural networks MS preferred or equivalent expertise in ML and AI Experience in optimization strategies, network design, training, and testing Performance analysis and evaluation methodologies Conversant with the state-of-the-art in natural language processing, computer vision and sensor technology Demonstrable successes as a machine learning practitioner 5+ years experience in the field of ML and AI Embedded experience preferred Knowledge of modern mobile hardware architectures preferred Not complacent with the status quo 218 Advisory Engineer, Machine Learning & AI Resume Examples & Samples . Identify and prove out the perfect synthesis of hardware and software for neural network performance that meets competing demands for low-power and real-time performance 5-7 years of experience Strong background in deep learning and convolutional neural networks MS or PhD preferred or 5+ years in ML and AI Experience in optimization strategies, network design, training, testing, performance analysis and evaluation methodologies Experience in the intersection of cloud computing and ML Good multitasking and communication skills The best candidates will not complacent with the status quo and are passionate about innovation and discovery 219 Machine Learning Internship Resume Examples & Samples . e.g. maker event participation, homebrew project presentation Already uses data to answer questions and make decisions – simple and complex ones Shares passion for technology and wants to understand what is under the hood of solutions Favors practical aspects of the science to solve real business problems 220 Machine Learning Software Engineer, Building Resume Examples & Samples . Apply expert software development skills to a wide range of ML-related coding projects Work with product managers to define use cases, and develop methodology and benchmarks to evaluate different approaches Knowledge developing and debugging in C/C++ and Java 221 Lumada Machine Learning Resume Examples & Samples . Managing and prioritizing backlog based on stakeholder & customer feedback Working with Architects on gathering business and technical requirements Responsible for decomposing backlog into user stories and wireframes Responsible for working daily with development team on requirements Understand business requirements to technical mapping Understand technical requirements to business requirements 5+ years of hands-on contribution in Software Engineering or related field Outstanding interpersonal and communication skills Experience with advanced IoT technologies Ability to convey complex technical information in a clear and concise manner Tech savvy, detail oriented, and highly driven 222 Director of Machine Learning Resume Examples & Samples . Lead and mentor a team whose responsibility is to develop prototype solutions at the intersection of healthcare and artificial intelligence Work with product managers, partners and peers to formulate the data analytics problems Interact with subject-matter experts across the clinical and financial domain at UPMC to discover and implement AI systems that help them do their job more precisely and more cost-effectively Communicate to executives the project activities, statuses, accomplishments, and strategic direction of the group Identify whitespaces in the healthcare market where commercialization opportunities exist for machine learning Communicate the results and methodology effectively within the team and to external stakeholders Evaluate new hardware and software products and technologies and participate in project assessments as necessary Implement and evaluate proposed model/methodology Promote and participate in professional self-development to stay up to date with new technologies and development approaches within the industry Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field from an accredited university is required PhD or M.S. in Computer Science, Applied Math, Statistics, Operations Research, Physics, Computational Biology, or other quantitative fields strongly preferred 10 years of experience in complex development environments, taking abstract concepts and ideas and formulating a detailed software engineering plan to deliver. Increasing responsibility throughout the candidate's career should be demonstrated 7 years of Experience leading teams of software developers and shipping product to actual customers Deep, hands-on understanding of essential modern programming/scripting languages: Java, Python, C++, Ruby Proficiency in at least one statistical modeling tools from among R, Matlab or Weka Any experience with Hadoop/YARN/Mesos/Spark/Elasticsearch/Kafka and building applications end-to-end 223 Machine Learning Resume Examples & Samples . Team up with the best people on the most challenging Financial Services programs Share knowledge with people known for their world-class expertise and insight Work with global clients, locally and internationally Be exposed to different business cultures in high-performing teams Help shaping the future of financial services Develop an international network of colleagues and clients that will last a lifetime A university degree with a minimum of a 2:1 (or equivalent), and ideally an MBA or MSc Relevant technical and delivery experience within, or working as a consultant/advisor to, a financial services organisation Experience in the following products: IBM Watson platform (Conversation & Text to speech), Azure Machine Learning or Google Cloud Machine Learning Experience in building AI and Machine learning models – Natural Language Processing (NLP), Natural Language Generation (NLG), Deep Learning (Voice and Image recognition) and Neural Networks Experience in building models in R, C++, Java or Python programming languages and libraries Experience in multiple tools/language/frameworks within the Big Data & cloud ecosystem (Hadoop, MongoDB, Neo4j, Spark, Hive, Hbase, Cassandra, etc.) Strong communication, presentation and business and technical writing skills The ability to provide excellent client service and manage and build strong relationships both internally and externally, coupled with a strong interest in further developing and integrating operations with technology skills Awareness of emerging issues, including regulations, industry practices and new technologies Experience in data analysis and using data to solve complex business problems Experience of developing data science capability Experience of working in an Agile Scrum environment Experience of using project monitoring software (i.e. JIRA & Confluence) 224 Software Engineer for Machine Learning Resume Examples & Samples . Strong desires to learn and explore new technologies and is able to demonstrate good analysis and problem solving skills EDA software development experience or IC design knowledge, especially in backend Know basic routing algorithms Good English communication skill, both oral and written 225 Predictive Analytics & Machine Learning Intern Resume Examples & Samples . Report development and analytics Learning new applications needed to complete assignments or support the execution of business objectives Job shadowing in other functional areas Performing additional duties as required Proficiency in executing analysis using R, Python, Excel, Weka, SAS, Java Knowledge of complex optimization algorithms such as ACO (Ant Colony Optimization) for optimizing results of predictions Expertise in predictive analytics, Natural Language Processing, statistical modeling, and/or data mining algorithms Knowledge and experience with large data sets, event streams and distributed computing (Hive/Hadoop, Spark, etc.) 0 GPA or above Ability to learn quickly and experience producing high quality work in short periods of time 226 Intern, Machine Learning Resume Examples & Samples . Near Phd (3rd-5th year) Strong background in Machine Learning, quantitative genomics, computational biology, bioinformatics, and/or biostatistics Some background in genomics 227 Predictive Modeling & Machine Learning Resume Examples & Samples . Collaborate with key internal and external partners from across the enterprise in order to develop and deploy a predictive modeling functionality Enable data-driven strategic decision-making, and find opportunities for product/service improvement and new product/service development Create and deliver tailored analytic solutions and lead complex projects related to a wide variety of business needs 228 Deep Leaning Expert for Machine Learning Development Resume Examples & Samples . Learn quickly new mathematical or technical methods Implement most recent algorithms and approaches for machine learning in collaboration with our data scientists and researchers Demonstrates up-to-date expertise in Software Engineering and applies this to development, execution, and improvement of action plans Initiates and participates in projects in the area of prediction, optimization, and processes using advanced statistical / mathematical approaches, in the enterprise environment Design best architecture and select the most appropriate modeling techniques and data visualization for big data analysis Iteratively test, refine and improve the models Strong background in Machine Learning (Deep Learning), especially in NLP and or Computer Vision required Experience in SQL, relational databases, database concepts, dimensional modeling and database design Proficient in one or more programming languages such as Python, Java, C++ Familiar with one or more machine learning modeling tools and platform Strong analytical and quantitative problem solving ability Strong Industry domain knowledge and experience preferred Must be able to work onsite in Palo Alto, CA 229 Manager, Machine Learning Resume Examples & Samples . A PhD in Statistics, Computer Science Machine Learning, or in a highly quantitative field 2+ years of experience managing technical teams 3+ years of hands-on experience in predictive modeling and big data analysis 3+ years of experience using R or Python 3+ years of experience managing technical teams Passion for people management and mentorship Track records of using technologies to deliver results Experience with distributed algorithms (Map-Reduce, MPI) Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts 230 UX Designer, Machine Learning Resume Examples & Samples . 3+ years of experience as a user experience designer or similar role, with at least 1 year experience working on enterprise tool design An online portfolio or samples of work demonstrating user-centered design solutions with measurable outcomes Ability to demonstrate designs with functional prototypes in HTML/CSS, Axure, InVision, or similar Understanding of HTML, CSS and JavaScript that informs design and interaction decisions Motivated to work in a start-up style environment, where rapid iteration is normal Visual design acumen demonstrated through owning product design end-to-end Practical knowledge of user-centered design methodologies, usability principles, web-based information architecture and designs Shown ability to work cross-team and synthesize feedback and input from business leaders, product management, and engineering Fluent in English, with excellent communication, presentation, and social skills Interest in machine learning, AI and similar technologies Ability to build rapport with partners, designers, developers and leaders Talent for crafting visionary and creative design solutions while maintaining user expectations through pattern consistency Experience crafting a v1 product vision Experience planning and facilitating user research activities Comfortable presenting to senior leadership (Directors and VPs) 231 Machine Learning Systems Intern Resume Examples & Samples . The candidate must be pursuing a BS degree in Computer Science, Computer Engineer, Electrical Engineer, Applied Mathematics or related field At the level of BS the candidate must have Permanent Right to Work in US Minimum 3 months of experience in Machine Learning and Deep learning Minimum 3 months of experience in software development Minimum 3 months of experience Linux, C++, C, Python 232 Machine Learning Software Researcher Resume Examples & Samples . Enabling machine learning algorithms to work on energy constrained mobile and wearable devices Advancing the state of the art in areas such as computer vision, sensor fusion, machine learning, object tracking, and motion planning Conducting research on efficient machine learning methods - supervised learning, unsupervised, reinforcement, and/or deep learning Research and prototype techniques and algorithms for object detection and recognition Developing robust software for integrating multiple sensors and tracking systems Ph.D. in Computer Science or Computer Engineering, focused on Artificial Intelligence, Machine Learning, or related technical field Professional research experience in industry or academia Strong understanding of microprocessor architecture Parallel computing programming experience (OpenCL/CUDA) is a plus Ability to port state-of-the-art applications on to hardware platforms and profile them to expose performance bottlenecks Low-level programming experience including assembly-level experience is a plus OS level programming experience including kernels, compilers, drivers, etc Experience with machine learning frameworks: Caffe, Torch, Theano or Tensorflow Proficient in C/C++ and Python Working knowledge of R/Matlab/Mathematica 233 Machine Learning Scientists Resume Examples & Samples . A PhD or equivalent degree in Statistics, Computer Science, Machine Learning, or in a highly quantitative field 2+ years of experience using R/SAS and SQL in a Linux/UNIX environment 2+ years of experience with Python 3+ years of industry experience in predictive modeling, machine learning and big data analysis Strong skills with Python and Java/C++ 2+ year distributed programming experience Track records of deliver results and strong ownership 234 Software Engineering Intern, Machine Learning Resume Examples & Samples . Design, develop and test FPGA-accelerated Machine Learning solutions Enable FPGA acceleration of open source deep learning frameworks like: Caffe, MxNet, and Tensorflow Work on porting existing deep learning applications to FPGA Solid foundation in data structures, computer arithmetic, algorithms and software design with strong analytical and debugging skills Solid coding skills with ability to write code in C++, Python, and other equivalent languages Course work and/or familiarity with Machine Learning models and Machine Learning infrastructure Experience or coursework in FPGA Digital Design or EDA optimization tools Experience with developing acceleration application using OpenCL or CUDA 235 Software Engineering Intern, Machine Learning Resume Examples & Samples . Design and develop FPGA-accelerated Machine Learning solutions Design and modify machine learning models: reduce computational complexity by model optimization, computation using lower precision arithmetic, data flow reordering for memory bandwidth optimizations Work closely with customers to port their deep learning requirements to FPGA Pursuing PhD/MS degree in Computer Engineering, Electrical Engineering, Computer Science, Mathematics, Statistics, or related field Good understanding of common families of Machine Learning models and Machine Learning infrastructure Experience with implementing machine learning computation framework on GPU, CPU or FPGA Experience with internals of one of more frameworks like Caffe, MxNet or Tensorflow 236 Machine Learning Software Intern Resume Examples & Samples . You will use machine learning and deep learning techniques to analyze and optimize Linux operating system components You will need to learn and leverage existing frameworks to model and train deep learning models on a variety of data You will be able to clean and process data for optimal training performance 237 SAP Machine Learning & IOT Resume Examples & Samples . Practical knowledge of working with scalable platforms for processing of huge data sets, and Ability to understand the data, associated processes and business implications, Scaling from minimum viable product up to shippable production code, Build and maintaining innovative new products from the ground-up Analyze customer requirements and assist them actively in optimizing their SAP IoT business applications Drive innovation to optimize, automate and standardize the operational delivery processes Deliver high quality and ensure stable operations For IOT Role, following requirements are must (You are expected to develop IOT-SAP Integrations) Experience with Web applications is must Excellent programming skills (e.g. JAVA or/and Java Script or/and HTML5) Experience with SAP UI5 is desired Experience with Hana Cloud Platform / Cloud foundry Experience with IBM Bluemix is big plus Experience with IoT /IoT 2.0 framework Experience with Event Stream Processor, Smart Data Streaming, HANA XS, OData Eligibility Requirements 238 Machine Learning Team Leader Resume Examples & Samples . Manages the machine team. Hires, coaches and provides directions. In charge of the team professional development Research of new technologies in the area of machine learning Receives defined requirements, identifies tasks and assigns them to direct reports. Makes day-to-day decisions within or for the team Drives collaboration with groups in the areas of machine learning and pattern recognition 239 SAP Labs Big Data & Machine Learning Challenge Resume Examples & Samples . Gain experience with real-world industrial scenarios in IoT and Big Data Work with tasks in HANA and HANA Vora and SAP Cloud Platform Analyze large data sets in the context of IoT Apply algorithms in Machine Learning for broad range of tasks and scenarios Students or fresh Graduates (preferences in Marketing, Management, Accounting, IT, Computer Science, etc.) Native Russian, Fluent English Basic programming skills using Python, C++ Basic knowledge of Linux OS, Linux shell, regular expressions, cmake infrastructure, autotools Good knowledge of MS Office (Excel, PowerPoint, Outlook) Teamwork skills 240 Senior Applied Researcher, Machine Learning Resume Examples & Samples . Experience applying machine learning to significant big data problems Experience with Scala, Java, C++, and/or Python Experience with machine learning software, such as Python Scikit, TensorFlow, and/or Spark MLLib Experience with Apache Hadoop or other distributed systems for Linux Experience with machine learning algorithms, such as neural networks/deep learning, SVM, Random Forest, linear regression, etc 241 Machine Learning / AI Engineer, Mobility Resume Examples & Samples . Adapts existing methods and procedures to create possible alternative solutions to moderately complex problems Primary upward interaction is with direct supervisor. May interact with peers and/or management levels at a client and/or within Accenture Determines methods and procedures on new assignments with guidance Decisions often impact the team in which they reside Manages small teams and/or work efforts (if in an individual contributor role) at a client or within Accenture Minimum 3 years of hands-on experience utilizing one or more of the following: statistical model design, data analytics, machine learning, or natural language processing Experience in modern deep learning approaches and natural language processing. Advanced proficiency with at least one statistical computing language for data analysis, such as R or Python Experience working in an agile methodology Proven success in contributing to a team-oriented environment 242 Machine Learning Software Dev Engineer Resume Examples & Samples . Computer Science fundamentals in object-oriented design, data structures, high-performance computing (HPC) Can translate user inputs to software requirements and design specifications and effectively communicate with team members Ph.D. with 3 years of relevant experience Experience with highly distributed systems Experience designing high performance software and algorithms for resource constrained IoT and mobile environments Proficiency training large scale models in, at least, one modern deep learning engine such as MXNet, Tensorflow, Caffe/Caffe2, Keras, PyTorch/Torch and Theano Experience in GPU, FPGA, DSP acceleration and performance tuning 243 Machine Learning Specialists / Engineers Resume Examples & Samples . Develop and implement Machine Learning algorithms for classification, clustering, prediction, or anomaly detection applications Perform experimental analysis efforts using state-of-the-art Machine Learning algorithms Conduct research in Machine Learning to enable development of new state-of-the-art algorithms for Laboratory problem domains Integrate algorithms within larger programmatic systems that require these capabilities and lead the development of advanced algorithms in support of R&D efforts Contribute to the fulfillment of projects and organizational objectives and fully function as a team member and/or task lead and/or principal investigator on multidisciplinary teams Prepare and present proposals corresponding to targeted new opportunities for the Laboratory Lead a team of researchers to produce high-quality deliverables and publish and present research results in peer-reviewed publications and at scientific conferences Act independently to provide technical leadership for specific projects or in an area of expertise PhD in Engineering, Computer Science, Applied Statistics, Applied Mathematics, Computational Biology, or a related field or the equivalent combination of education and related experience Subject matter expert knowledge and expert level experience applying and developing algorithms in one or more of the following Machine Learning areas/tasks: deep learning, unsupervised feature learning, reinforcement learning, zero- or few-shot learning, multimodal learning, natural language processing, ensemble methods, scalable density estimation, scalable online inference, and probabilistic graphical models Significant experience providing expert level technical leadership for Machine Learning and statistical analysis projects and providing solutions to highly complex problems Significant experience using one or more higher-level programming languages such as C/C++, Java/Scala, or Python to lead the application and development of Machine Learning algorithms Significant experience using one or more scientific analysis and prototyping environment such as R, MATLAB, or the SciPy Stack to lead the application and development of Machine Learning algorithms Significant experience leading complex projects with responsibility for budgets, schedules, and deliverables; experience with project management and resource allocation Experience mentoring individuals and teams Expert communication skills necessary to author technical and scientific reports, publications, invited papers, and to deliver scientific presentations and provide advice to senior management Exceptional track record in program development and team management Extensive experience in developing and writing award-winning technical proposals and an established publication record Deep Learning expertise and experience with Deep Learning models and libraries and broad knowledge of all interdisciplinary areas that interact with Machine Learning 244 Software Engineer, Machine Learning Resume Examples & Samples . Previous software engineering experience Passion to learn ML Experience with some of the following: Java (or Python), HBase or Hadoop/Spark Bonus points for: Tensorflow, Sklearn, Jupyter or NumPy 245 Machine Learning POC Intern Resume Examples & Samples . Help define and own creation of data collection protocols and document, support, and train users of the protocol Collection and scrubbing of data collected, building prototype to prove concepts of use-cases Develop embedded FW and Software Excellent communication, interpersonal and problem solving skills Demonstrated attention to detail and can take direction and follow-through on assignments Embedded controller such as Intel Curie and machine learning Python, and C programming languages Senor data processing, BLE stack 246 Principal, Machine Learning Resume Examples & Samples . We are looking for both strong data sense and the technical background to help us build the most compelling data stories for our clients & prospects Work with Data Designers to select & use the right tools or partners for the right project Using state of the art big data user interfaces to sift through billions of rows of data to answer challenging business questions Help design and analyze AB and multivariate experiments Stay abreast of advances in the field that will help us grow 247 Data Analytics & Machine Learning Sme-bell Labs Consulting Resume Examples & Samples . In-depth expertise in data analytics and machine learning Ability to learn fast - new concepts, technology, business value propositions Familiarity with modeling tools including Excel, and software tools such as Python, Perl, VBA, JAVA, JavaScript, R, Linux, HTML5, PowerShell Ability to draw conclusions from model and simulation runs, develop and communicate insights needed to advise customers' technical and business leaders Excellent oral, written and presentation skills Deep understanding of telecom/ICT networks and services and transformation complexities (technology, operations and business economics) Experience in working across diverse teams to deliver to aggressive targets Minimum M. Sc. or M.S. in Engineering, Computer Science, Physics or related field 248 Senior Machine Learning SDE SDE Resume Examples & Samples . 7+ years professional experience building and operating scalable distributed systems across the full software lifecycle including design, implementation, testing, operations, and maintenance Hands-on experience across front-end user interfaces, business logic, and data tiers Experience working with modern tools for big data storage and analysis (e.g., AWS, Apache Spark, Hadoop, SQL, NoSQL) 249 Machine Learning Products Marketing Manager Resume Examples & Samples . Drive marketing strategy and tactical planning for new growth areas Working with development teams, develop product plans by collecting and synthesizing customer requirements, use cases, and personas; develop multi-year roadmaps informed by the medium- to long-term direction and opportunities; and collaborate with technical marketing and development teams in adjacent areas Plan and deliver go-to-market content to drive awareness and adoption of your products, including launch, web pages, videos, and examples Produce content and messaging for global digital marketing campaigns Support the worldwide field sales and application engineers with materials and training necessary to raise awareness and engage with business sponsors and end users. These include customer presentations, differentiators, and other selling tools and tactics. Validate the materials and tactics through on-site customer visits and calls Project thought leadership for machine learning with MATLAB by presenting at conferences, briefing analysts and editors, and networking with influencers on social channels Measure business impact for your product area and develop plans to enhance penetration and growth in both commercial industries and academia A bachelor's degree and 7 years of professional work experience (or a master's degree and 5 years of professional work experience, or a PhD degree) is required Proficiency with product management Experience with product marketing Experience working with software development, marketing, application engineering, and sales teams in a highly collaborative, consensus-based team environment Command of principles of machine learning, statistical analysis, deep learning, and mathematical modeling Experience in machine learning and statistical analysis on large size data using Spark or Hadoop Knowledge of applications of machine learning to application areas such as computer vision, predictive analytics, risk analytics, health monitoring, or IoT Knowledge of community libraries and platforms for deep learning, such as TensorFlow, Keras, Caffe, Theano, Torch, or Matconvnet Knowledge of MATLAB, R, Python, or SAS Solid quantitative ability and strong overall marketing, research, and planning skills Candidate should expect to travel about 20% of the time 250 Big Data Designer, Machine Learning Resume Examples & Samples . Would normally lead on a specific deliverable of a small/medium scale project or implement smaller less complex projects to achieve required business benefits and manage to budget, timescales and quality Could be responsible for direct line managing and developing of Analysts, but more likely to indirectly manage people to deliver specific tasks or projects To ensure operational procedures are in place, maintained and followed as appropriate May involve liaising with internal, external and third party suppliers Broad understanding of VOIP telephony services, both network and CPE Must have a strong technical understanding of DECT technology from GAP through to CAT-iq 2.1/3.0 including their ETSI specifications Experience of integrating of these services in a multi-vendor environment between Handsets and Bases Working knowledge of Home Gateway standards including, but not restricted to: IPv4/IPv6, PPP, IPoE, Wifi, UPnP / Multicast, EoGRE, TR069, TR181 Proven technical vendor management and stakeholder management skills Download Machine Learning Resume Sample as Image file Related Job Titles. 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Result 9
TitleMachine Learning Engineer Resume Sample - Towards Data ...
Urlhttps://towardsdatascience.com/machine-learning-engineer-resume-sample-ea7a4951f030
DescriptionMachine Learning Engineer Resume Sample ... The first step to every job hunt is your Resume also called CV. Today I will show you my personal CV and walk ...
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Organic Position9
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Result 10
TitleMachine Learning Engineer Resume Example - LiveCareer
Urlhttps://www.livecareer.com/resume-search/r/machine-learning-engineer-d282aa9ca3c94cbaa70594772952db9b
DescriptionA machine learning engineer passionate about cutting-edge technology and solving real-world problems, with previous experience in finance managing risk, leading ...
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TitleMachine Learning Engineer Resume: Templates, Examples ...
Urlhttps://www.resumegiants.com/examples/machine-learning-engineer-resume/
DescriptionCreate the perfect resume for a machine learning career and learn how to impress recruiters with your skills, education, and experience.
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TitleMachine Learning Engineer Resume Examples (2022 Guide) | BrainStation®
Urlhttps://brainstation.io/career-guides/machine-learning-engineer-resume-examples
DescriptionA machine learning resume is used to apply for machine learning jobs. A good resume is crucial for landing an interview for a Machine Learning Engineer job
Date
Organic Position12
H1Machine Learning Engineer Resume Examples
H2What are Machine Learning Engineer Resumes?
Machine Learning Engineer Resumes – a Step-by-Step Guide
Getting Started – What is the Purpose of the Resume?
How to Create an Outline for a Machine Learning Resume
What to Include in Your Machine Learning Engineer Resume?
What Skills Should You Put on a Machine Learning Engineer Resume?
Machine Learning Engineer Resume Template
Kickstart Your Machine Learning Engineer Career
H3Become a Machine Learning Engineer
Thank you!
RECOMMENDED COURSES FOR MACHINE LEARNING ENGINEER
H2WithAnchorsWhat are Machine Learning Engineer Resumes?
Machine Learning Engineer Resumes – a Step-by-Step Guide
Getting Started – What is the Purpose of the Resume?
How to Create an Outline for a Machine Learning Resume
What to Include in Your Machine Learning Engineer Resume?
What Skills Should You Put on a Machine Learning Engineer Resume?
Machine Learning Engineer Resume Template
Kickstart Your Machine Learning Engineer Career
BodyMachine Learning Engineer Resume ExamplesBrainStation’s Machine Learning Engineer career guide is intended to help you take the first steps toward a lucrative career in machine learning. Read on for Machine Learning Engineer resume examples that will help you prepare your job application. Become a Machine Learning Engineer. Speak to a Learning Advisor to learn more about how our bootcamps and courses can help you become a Machine Learning Engineer.Thank you!We will be in touch soon. What are Machine Learning Engineer Resumes? A machine learning resume is a document used to apply for a machine learning job. A strong resume is essential for securing an interview for a Machine Learning Engineer position. Resumes should list your skills, experiences and qualifications. Through your resume, an employer should see why you are a great candidate for the role. Machine Learning Engineer Resumes – a Step-by-Step Guide. There are a few steps you should take before you start writing your machine learning resume, as well as several best practices to keep in mind while you write. Before You Write Research the company: Resumes and cover letters need to be tailored to the position you are applying for. To do this, you first need to learn more about the company. Take a look through their website, social media and news or press releases. By getting a sense of their work, values and objectives, you can customize your resume to address their specific needs. Compose a master resume: Compile a list of all your work-related accomplishments in one document. Your master resume acts as a reference guide for you. When you begin drafting your resume, select the experiences that are most relevant to the job posting. As You Write Be concise: Your machine learning resume should be a one-page document. Hiring Managers may be reviewing hundreds of applications, so keep your resume short and focused. Choose a clean template: The layout of your resume should be organized, readable and aesthetically pleasing. The design should not distract from the content. Use bullet points and headings: Keep your resume organized with clear headings and bullet points. Remember to include ample white space—you don’t want your resume to be too cluttered. Opt for action verbs: Choose impactful action verbs that highlight your achievements. Examples of action verbs include: solved, accelerated, deployed, reduced and conceptualized. Emphasize your successes: Use accomplishment statements that follow the formula action verb + task + result. For example, “Developed model to predict stock prices with 98% accuracy, enabling company to make informed investments.” Add numbers and key metrics: To show employers the impact of your work, include concrete numbers and stats wherever possible. Quantify your accomplishments so the company can clearly see the value you would bring. Edit and review: Go through your resume and check for spelling, grammar or typographical mistakes. Keep your content to the point and eliminate any superfluous descriptions. Ask for feedback: Send your resume to a trusted colleague, friend, family member or mentor. It can be helpful to have an outside perspective and a fresh pair of eyes. Getting Started – What is the Purpose of the Resume? A resume should show why you are the best candidate for a Machine Learning Engineer job. Your resume is an introduction and pitch to the employer—it is your way of convincing the company that you would be an asset. Your resume should be framed around how you can help the company achieve their goals. A strong resume will ultimately help you secure an interview. How to Create an Outline for a Machine Learning Resume. A good outline to follow for your machine learning resume is: Header: List your contact information (name, phone number, email) and include links to your portfolio and/or GitHub profile.Profile/Summary: Emphasize key points from your resume that show why you are the best candidate for the role.Experience: Outline your top machine learning successes.Projects: Highlight relevant machine learning projects.Education: Include degrees/certificates/training.Skills: Include relevant technical skills that match the job description.Extra Sections: Add in conferences, published papers, awards and other activities or interests. What to Include in Your Machine Learning Engineer Resume? Your Machine Learning Engineer resume should include a profile, work experience, machine learning projects, technical skills, training/education and extras. Profile: A strong profile/summary highlights your best features. Your profile should convince the Hiring Manager to keep reading the rest of your resume. In two to four sentences, tell the employer who you are, describe your machine learning successes and explain what you would bring to the role. Work experience: List your most relevant work experience in reverse chronological order, with your most recent experience first. Each experience should include your job title, the company and dates you were employed. In a few bullet points, describe your main accomplishments. Remember to focus on successes. For example, “Used logistic regression models to make predictions” doesn’t say much about your work. To reframe it as a success, you could write, “Applied logistic regression model to predict product sales to within 2%.” Education: Include post-secondary degrees and any other certifications. You can also highlight relevant coursework, academic achievements or scholarships. Projects: Machine learning projects are evidence of your skills—they show employers what you can achieve. Include the title, a link to the project and your role. Provide a brief description of the project, along with tools used. Skills: List your technical skills that match what is listed in the job description. Extras: Include additional sections that will help you stand out. For example, you could add in conferences attended, papers published or awards received. These also help show your passion and dedication to your craft. What Skills Should You Put on a Machine Learning Engineer Resume? The skills you include on your Machine Learning Engineer resume should match the ones listed on the job description. Keep in mind that some companies use automated resume scanning software. To make sure you pass that initial screen, you will want to include key skills or phrases from the job description. While skills will vary depending on the position, there are a few common skills that most Machine Learning Engineers should have. Here are a few skills that employers often look for in candidates: Data structuresData modelingData visualizationPredictive modelingStatistical modelingRegressionClustering and classificationWeb scrapingTensorflowPytorchKerasNumpyPandasSciKit LearnMATLABExplanatory analysisNatural Language ProcessingPySpark.MLJupyter Notebook You will also be expected to know programming languages, such as: C++PythonJavaRLispProlog Machine Learning Engineer Resume Template. [NAME][Phone Number][Email][GitHub /portfolio link] SUMMARY/OBJECTIVE Skilled machine learning engineer with expertise in [area of expertise]. Successfully [major machine learning accomplishment or project]. Eager to bring experience in [top skills] to help [company]. EXPERIENCE [Job title, Company][Month, Year – Month, Year] · [Action word] [skill/task] [result/impact]· [Action word] [skill/task] [result/impact]· [Action word] [skill/task] [result/impact] [Job title, Company][Month, Year – Month, Year] · [Action word] [skill/task] [result/impact]· [Action word] [skill/task] [result/impact]· [Action word] [skill/task] [result/impact] EDUCATION [Degree earned, School name][Graduation date] · [Relevant courses]· [Academic achievements] SKILLS · [Technical skills]· [Programming languages] PROJECTS [Project], [Role][Brief description of project] ADDITIONAL ACTIVITIES · [Conferences]· [Volunteer experience] PreviousMachine Learning Engineer Cover Letter ExamplesNextMachine Learning Engineer Interview Questions Get startedKickstart Your Machine Learning Engineer Career. We offer a wide variety of programs and courses built on adaptive curriculum and led by leading industry experts.Work on projects in a collaborative settingTake advantage of our flexible plans and scholarshipsGet access to VIP events and workshopsSpeak to a Learning AdvisorRECOMMENDED COURSES FOR MACHINE LEARNING ENGINEER. BOOTCAMPData Science BootcampThe Data Science bootcamp is an intensive course designed to launch students’ careers in data. CERTIFICATEPythonThe Python certificate course provides individuals with fundamental Python programming skills to effectively work with data. certificateData Science CourseTaught by data professionals working in the industry, the part-time Data Science course is built on a project-based learning model, which allows students to use data analysis, modeling, Python programming, and more to solve real analytical problems. We use cookies to improve your experience on our site, and to deliver personalized content. 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Result 13
TitleMachine Learning Resume Examples [Also for an Engineer]
Urlhttps://resumelab.com/resume-examples/machine-learning
DescriptionNeed a machine learning resume that breaks algorithms? Get one with a machine learning engineer resume sample that features OpenCV machine learning
DateJun 5, 2021
Organic Position13
H1Machine Learning Resume Examples [Also for an Engineer]
H2Machine Learning Resume Example
1. Choose the Right Machine Learning Resume Format
2. Start With a Compelling Resume Summary
3. Create the Perfect Machine Learning Job Descriptions and Skills Section
4. Leverage Your Education to the Max
5. Stack Your Machine Learning Resume With Added Sections
Key Points
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Free Resume Templates—Download & Start Making Your Resume
50+ Free Microsoft Word Resume Templates to Download
18 Best Resume Templates for All Professions [Fill In & Download]
H3Machine Learning Resume Format
Machine Learning Resume Example—Summary
Machine Learning Resume Job Description
Machine Learning Professional Skills for a Resume
Machine Learning Resume Example—Education
Machine Learning Engineer Resume Sample—Additional Sections
H2WithAnchorsMachine Learning Resume Example
1. Choose the Right Machine Learning Resume Format
2. Start With a Compelling Resume Summary
3. Create the Perfect Machine Learning Job Descriptions and Skills Section
4. Leverage Your Education to the Max
5. Stack Your Machine Learning Resume With Added Sections
Key Points
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Free Resume Templates—Download & Start Making Your Resume
50+ Free Microsoft Word Resume Templates to Download
18 Best Resume Templates for All Professions [Fill In & Download]
BodyMachine Learning Resume Examples [Also for an Engineer]You’re a diviner of data, an expert trainer of ML dragons. Make sure your machine learning resume does your skills justice. Read on to find out how.Bart TurczynskiEditor-in-Chief05/06/2021 Copy Facebook LinkedIn TwitterCopied successfully Something went wrong, try again. Abstract: Machine learning is at the heart of common artificial intelligence applications like email filtering and computer vision. The purpose of your machine learning resume is to show you’ve got the theoretical knowledge and programming skills to push ML boundaries as well as the soft skills to be a productive member of a team.You’re no stranger to sorting and filtering data on an inhuman scale. Finding meaningful patterns and useful correlations in tangled masses of information. Somewhere, a human recruiter will be sorting through ML resumes— Filtering and eliminating and then comparing and assessing— Until they find that one candidate that ticks all the boxes better than anyone else. Just like preparing a data set— Prepare your machine learning resume so that it has the best possible chances of getting through. In this guide: A machine learning resume sample better than most.How to create the perfect ML job descriptions for your resume.How to write a resume for machine learning jobs that stands out.Expert tips and examples to boost your chances of landing a job in machine learning. Save hours of work and get a resume like this. Pick a template, fill it in. Quick and easy. Choose from 18+ resume templates and download your resume now.  Create your resume now What users say about ResumeLab:I had an interview yesterday and the first thing they said on the phone was: “Wow! I love your resume.”PatrickI love the variety of templates. Good job guys, keep up the good work!Dylan My previous resume was really weak and I used to spend hours adjusting it in Word. Now, I can introduce any changes within minutes. Absolutely wonderful!GeorgeCreate your resume now Looking to share your knowledge or launch a technical writing side hustle? See our guides: Technical Writer Resume SampleEngineering Resume SampleIT Resume SampleTechnical Resume SampleCyber Security Resume SampleIT Project Manager Resume SampleDevOps Resume SampleSoftware Engineer Resume SampleGraduate School Application SampleEntry-Level Software Engineer Resume SampleData Scientist Resume SampleComputer Science Student Resume SampleProgrammer Resume SampleResume Samples for All Jobs (2021) Machine Learning Resume Example.  Thomas HowardMachine Learning Engineer Personal Info Phone: 419-763-3201E-mail: [email protected]/in/thomashhoward Summary Creative machine learning engineer with 6+ years’ experience working in consumer data-mining and computer vision. Seeking to bring technical expertise and business-minded approach to bear on Shop-U-Track’s current projects. At Hi-Viz Systems, developed and shipped 11 OpenCV machine learning solutions and helped to generate seven patents. Experience  Machine Learning EngineerHi-Viz SystemsMarch 2017–presentDesigned OpenCV machine learning algorithm that evaluated to 82% efficiency.Developed and shipped 11 OpenCV machine learning solutions for automatic predictions and decisions.Improved and maintained common tools and infrastructure, freeing up over 10 labor hours per week in the long run.Helped to generate seven patents as part of a team of four machine learning engineers. Machine Learning InternSnoopCorpMay 2015–February 2017Used Juniper router data to develop machine learning models that identify anomalies with 94% accuracy and 0.1% false positives.Built predictive models with decision trees to track users preemptively, up to three URLs ahead.Identified and built 11 new datasets to enhance models and decision making.Developed, validated, and implemented newly created models into three proofs of concept. Education  MEng in Artificial Intelligence, University of Cincinnati2013–2015Pursued a passion for business studies.Excelled in applied mathematics and statistics coursework. BS in Artificial Intelligence, Carnegie Mellon University2009–2013 Professional Memberships Association for the Advancement of Artificial Intelligence (AAAI)Data Science Association Programming Languages PythonJavaCC++JavaScriptRScalaJulia Key Skills  Clustering algorithmsDecision treesEnsemble methodsIndependent Component AnalysisLogistic RegressionCommunicationCritical thinkingProblem solvingTeamworkProject management Now here’s how to write a machine learning resume they’ll love: 1. Choose the Right Machine Learning Resume Format.  Don’t be like that intern— Feeding in randomly formatted data sets and wondering why they’re not being parsed. It’s not even a matter of satisfying Applicant Tracking Systems (ATSs)— People won’t want to deal with resume format outliers. Make sure your resume format is exactly what recruiters expect to see: Machine Learning Resume Format.  Use the reverse-chronological resume formatand put your most recent successes first. If you work mostly as a freelancer, you might want to consider the functional (skills-based) resume format.For a neat resume layout, pick a proven resume font like a Noto, Garamond or Arial in 11–12 pt.Use one-inch resume marginsand lots of white space.Submit a one-page resume. Go to a two-page resume only if you have 15+ years’ experience.Outline your resume like this: Header, Summary, Experience, Education, and Skills.Perfect resumes are ATS-compatible. So choose a modern resume template, but make sure it doesn’t have visual elements such as infographics.Expert Hint: How to write a resume fast? Tailor it to the job description. Consult the job ad at every step of the process. Include only those things that are relevant to the job.2. Start With a Compelling Resume Summary.  Every resume should start with a resume profile. A profile can be a resume objective or summary. You may have written resume objectives for entry-level jobs, but— There are no entry-level machine learning jobs. Even if you’re applying for your first ML job or an ML internship— You have a lot of relevant experience—in AI, software engineering, data science, and so on. So— Start your machine learning resume with a resume summary. Use: One adjective (efficient, inventive, industrious)Job title (Machine Learning Engineer)Years of experience (3+, 7+)How you intend to help (push OpenCV-based development to next stage)Your most impressive 2–3 achievements (developed and shipped 11 OpenCV machine learning solutions, helped to generate seven patents) These machine learning resume summary examples show how: Machine Learning Resume Example—Summary. Good ExampleCreative machine learning engineer with 6+ years’ experience working in consumer data-mining and computer vision. Seeking to bring technical expertise and business-minded approach to bear on Shop-U-Track’s current projects. At Hi-Viz Systems, developed and shipped 11 OpenCV machine learning solutions and helped to generate seven patents.Bad ExampleLogically minded machine learning engineer with 6 years’ experience. Seeking to expand on ML and AI expertise with Shop-U-Track. At Hi-Viz Systems, developed and shipped OpenCV machine learning solutions and helped to generate patents.Which would you hire? The first example is data-driven— It sticks to concrete facts, and backs them up with numbers. It’s focused on what the candidate can do for the company, not the other way around.Expert Hint: Wanting to start writing your resume from the beginning is totally understandable, but it’s better to write your qualifications summary last. You’ll be able to do a much better job this way.3. Create the Perfect Machine Learning Job Descriptions and Skills Section.  Your machine learning job descriptions have one job: To get you invited to a job interview. Achieve this by describing what you were able to do for previous employers. Make your resume work history section a showcase of your achievements. How to write a job description for machine learning jobs: Go back over the job ad.Note any requisite machine learning skills and duties.Think of times you’ve used those skills to bring value to employers.Write resume bullet points that describe and quantify those times. These machine learning resume examples show how: Machine Learning Resume Job Description. Good ExampleMachine Learning EngineerHi-Viz Systems2017–presentDesigned OpenCV machine learning algorithm that evaluated to 82% efficiency.Developed and shipped 11 OpenCV machine learning solutions for automatic predictions and decisions.Improved and maintained common tools and infrastructure, freeing up over 10 labor hours per week in the long run.Helped to generate seven patents as part of a team of four machine learning engineers.Bad ExampleMachine Learning EngineerHi-Viz Systems2017–presentDesigned efficient OpenCV machine learning algorithm.Developed and shipped OpenCV machine learning solutions for automatic predictions and decisions.Improved and maintained common tools and infrastructure.Helped to generate patents as part of a small team of machine learning engineers.Same candidate, same situations, similar descriptions— Very different effects. The first one leverages quantified resume achievements for maximum impact. Both do a good job of starting each bullet point with a resume power word, though.Expert Hint: Got employment gaps on your resume? It’s not unusual, so don’t try to hide them. If you feel they need some explanation, do it in your cover letter.That’s all for your work experience— Now it’s time to add a resume skills section. The trick here: Be selective. Filter your machine learning skills through the job ad— The skills list below is just a seed: Machine Learning Professional Skills for a Resume.  Clustering algorithmsDecision treesEnsemble methodsIndependent Component AnalysisLogistic RegressionNaïve Bays ClassificationsOrdinary Least Squares RegressionPrincipal Component AnalysisSingular Value DecompositionSupport Vector MachinesCommunicationCritical thinkingDecision makingFlexibilityInterpersonal skillsLeadershipOrganizationProblem solvingTeamworkTime management Make sure to add both soft and technical skills to your resume. Aim at a list of 5-10 skills. The ResumeLab builder is more than looks. Get specific content to boost your chances of getting the job. Add job descriptions, bullet points, and skills. Easy. Improve your resume in our resume builder now.  CREATE YOUR RESUME NOW Nail it all with a splash of color, choose a clean font, highlight your skills in just a few clicks. You’re the perfect candidate and we’ll prove it. Use the ResumeLab builder now. 4. Leverage Your Education to the Max.  No machine learning resume is complete without an education section. Recruiters are interested, first and foremost, in what you can do— And your work history and academic background give them the best insight into this. Keep your education section clear and concise: include degree names (with majors), school names, and years attended. Add bullet points with thesis topics (for research Masters and PhDs), achievements, and any other facts that point to your machine learning skills. This machine learning resume sample shows how: Machine Learning Resume Example—Education. Good ExampleMEng in Artificial Intelligence, University of Cincinnati2013–2015Pursued a passion for business studies.Excelled in applied mathematics and statistics coursework. BS in Artificial Intelligence, Carnegie Mellon University2009–2013Applying for an ML internship or your first ML job?  Add more bullet points detailing projects, relevant coursework, and accomplishments that show how you’re on a collision course with a successful career in machine learning. 5. Stack Your Machine Learning Resume With Added Sections.  It’s taken you quite a while to gain the expertise you need to work in machine learning. There’s a lot that won’t fit into the categories of work experience, education, and skills— Add one or two extra resume sections to flesh out the picture: Additional ActivitiesForeign LanguagesCourses CompletedAwardsHobbies and Personal InterestsVolunteering on a ResumeCertificationsProfessional ReferencesMachine learning projects These two ML resume examples show how there’s a right way and a wrong way to do this: Machine Learning Engineer Resume Sample—Additional Sections. Good ExampleProfessional Memberships Association for the Advancement of Artificial Intelligence (AAAI)Data Science Association Programming Languages PythonJavaCC++JavaScriptRScalaJuliaBad ExampleComputer Skills LibreOfficeMicrosoft OfficeFirefoxThunderbirdTouch-typing Hobbies Flying dronesRecovering data off erased HDDsBird watchingThe second gets a couple of important things wrong: It’s not really relevant to the job at hand. Hobbies and interests can be a great addition, but they have to be directly and demonstrably relevant. And including the most basic of computer skills in your resume doesn’t make much sense when you’re able to pick up any new programming language within a day (or two for Haskell). One last if statement— Always include a cover letter with your machine learning resume, unless you’ve been explicitly asked not to. If you don’t, you run the very real risk of having your machine learning resume rejected at the outset. And if you’re emailing your job application, your cover letter doesn’t have to be even one page long. Double your impact with a matching resume and cover letter combo. Use our cover letter builder and make your application documents pop out.  CREATE YOUR COVER LETTER NOW Want to try a different look? There’s 18 more. A single click will give your document a total makeover. Pick a cover letter template here. Key Points.  For a machine learning engineer resume that gets interviews: Use the machine learning resume template given at the beginning. You won’t find a cleaner approach.Put machine learning resume achievementsin your summary, work history, and education sections to let the facts do the talking for you.Select for the right machine learning skills. The job ad and your experience are the only data sets you’ll need here.Write a machine learning cover letter. Showcase your achievements as you demonstrate your communication skills. Need more data points on how to write a winning machine learning resume? Leave any questions, comments, and feedback down below and we’ll be happy to get back to you.Rate my article: machine learningThank you for votingAverage: 5 (3 votes)Written by Bart TurczynskiFollowBart Turczynski is a career expert and the Editor-in-chief at ResumeLab. His career advice and commentary has been published by Glassdoor, The Chicago Tribune, Workopolis, The Financial Times, Hewlett-Packard, and CareerBuilder, among others. Bart’s mission is to promote the best, data-informed and up-to-date career advice on ResumeLab’s blog as well as through numerous online communities and publications. At ResumeLab, Bart manages a large team of career experts and editors in delivering top-quality, unique content. Bart’s life-long passion for politics and strong background in psychology makes all the advice published on ResumeLab unique, accurate, and supported by detailed research.Please enable JavaScript to view the comments powered by Disqus.Was it interesting? Here are similar articles. Free Resume Templates—Download & Start Making Your Resume. If you’re looking for a free resume template for your next resume, you’re right where you need. Word, Google Docs, InDesign resume templates. We have them all. And much more.Maciej DuszyńskiCareer Expert31/03/202150+ Free Microsoft Word Resume Templates to Download. A Microsoft Word resume template is a tool which is 100% free to download and edit. It can be used to apply for any position, but needs to be formatted according to the latest resume / curriculum vitae writing guidelines. Enjoy our curated gallery of over 50 free resume templates for Word. Each template has been cherry-picked by a career expert.Maciej DuszyńskiCareer Expert02/09/202118 Best Resume Templates for All Professions [Fill In & Download]. What are the best resume templates? Easy. The ones that will get you past the ATS scanning stage, dazzle the recruiter, and get you the job. Well, you’ve just found them.Maciej DuszyńskiCareer Expert22/12/2021
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Result 14
TitleMachine Learning Resume - Guide & Sample | upGrad blog
Urlhttps://www.upgrad.com/blog/machine-learning-resume-guide-sample/
DescriptionMaking a resume is a pain for most job seekers. We will break down each point here to clarity so that the process becomes buttery smooth for you. That’s exactly what this article talks about
DateMar 5, 2021
Organic Position14
H1Machine Learning Resume – Guide & Sample
H2What makes a good Machine Learning Resume?
Structure of a Sample Machine Learning Resume
Dos and Don’ts of a Resume
Before you go
What skills are required for Machine Learning?
How to build a good machine learning resume?
What is the future for machine learning?
Lead the AI Driven Technological Revolution
Related Articles
Beginners Guide to Bayesian Inference: Complete Guide
How to Perform Multiple Regression Analysis?
What is Probability Sampling? Definition, Methods
Related Articles
Beginners Guide to Bayesian Inference: Complete Guide
How to Perform Multiple Regression Analysis?
What is Probability Sampling? Definition, Methods
H3The ATS Factor
Summary
Contact Details and Social Profiles
Work Experience
Personal Machine Learning Projects
Skills
Hackathon Achievements
Education
Our Trending Machine Learning Courses
Our Popular Machine Learning Course
H2WithAnchorsWhat makes a good Machine Learning Resume?
Structure of a Sample Machine Learning Resume
Dos and Don’ts of a Resume
Before you go
What skills are required for Machine Learning?
How to build a good machine learning resume?
What is the future for machine learning?
Lead the AI Driven Technological Revolution
Related Articles
Beginners Guide to Bayesian Inference: Complete Guide
How to Perform Multiple Regression Analysis?
What is Probability Sampling? Definition, Methods
Related Articles
Beginners Guide to Bayesian Inference: Complete Guide
How to Perform Multiple Regression Analysis?
What is Probability Sampling? Definition, Methods
BodyMachine Learning Resume – Guide & Sample by Pavan Vadapalli Director of Engineering @ upGrad. Motivated to leverage technology to solve problems. Seasoned leader for startups and fast moving orgs. Working on solving problems of scale and long term technology…Mar 5, 2021 Home > Artificial Intelligence > Machine Learning Resume – Guide & SampleIn the current times, getting a Machine Learning job seems quite difficult seeing so much competition around. A Machine Learning Engineer/Data Scientist job posting gets more than 200 applicants within the first day itself. So how to tackle this situation so that you get an awesome Machine Learning job quickly? Making a resume is a pain for most job seekers. We will break down each point here to clarity so that the process becomes buttery smooth for you. That’s exactly what this article talks about.By the end of this tutorial, you will know the following:What makes a good Machine Learning resumeStructure of a sample resumeIn-depth analysis of each section of the resumeDo’s and Don’ts of the resumeLet’s get straight to it.Table of Contents What makes a good Machine Learning Resume?The first step to every job application is the resume. A resume is nothing but a medium of marketing yourself to the recruiter. It’s just equivalent to saying “Hey, here’s what all I have and done. And I’m awesome”. But that’s what an average resume does and miserably fails. A good resume should be a crisp, concise and very structured document that shows why you are right for the job you’re applying for. The ATS Factor. Most of the job postings get 100s of resumes. So do you think the recruiter goes through every resume they receive? No. Most of the recruiters use an ATS (Applicant Tracking System) whose first task is to rate the resumes according to their content. Once your resume aces the ATS barrier, it goes to the recruiter’s hands who scans your resume for a few seconds. That’s it. Just a few seconds. So our aim here is to make a resume that first passes the ATS barrier and then impresses the recruiter. And then you’re highly likely to receive a call from them. Structure of a Sample Machine Learning Resume.  Below is a sample of a Machine Learning resume that we will discuss. We’d suggest you follow along and make your own resume as you read through. The first and foremost thing to keep in mind while making your resume, and also the mistake which 8/10 people make while making their resume is – your resume doesn’t need to be of more than a page. Making your resume unnecessarily 2 or even 3 pages long will in no way increase your chances of getting the call. Did you win a race in 7th standard? The recruiter doesn’t care.  The whole idea here is to only include relevant information.The template shown above is fairly good and tested one. However, you can always make a template of your choice. Also, you can add/remove the sections as it fits your profile and experience. The only thing to be kept in mind is, the simpler it is, the better. Let’s go over each section one by one.Summary. The summary is not really a necessary one if you don’t have any professional experience. The only motive of the summary is to tell the recruiter about your background in 1 or 2 lines. If you are a fresher and don’t have any professional experience, you can skip this one. You can include this even if you have internship experience. The major mistake that most of the applicants make is, adding unnecessary adjectives into the summary. For example:“A highly motivated professional with proven work experience in Machine Learning. A hard-working, goal-oriented and proactive person. I am a team player who is a problem solver and possess leadership skills. Looking for a challenging role to showcase my skills and grow.”This summary is not at all what the recruiter wants to see the first thing in your resume. And the sad truth is that it is what is present in most of the resumes. Dumping in adjectives like “Highly motivated”, “team player”, etc. will not make the resume stand out. It only makes it more redundant and wastes crucial space. The summary section should talk about how much experience you have, what major skills you possess and what kind of roles you’re looking for.Contact Details and Social Profiles. This section should contain your phone number, your email address and the current city you’re living in. Do NOT include your whole address up to your PIN code. The recruiter has no interest in it. Keep the location details just to the city, or at most, the state. Remember, we will only include relevant information. Try to put a professional-looking email address and not something which might put a bad impression on the recruiter. Make a new one if you don’t already have it. You’re going to use that for your entire life.Put in your LinkedIn profile after customizing the link. Add your GitHub profile only if it has a good amount of projects and activity. Adding a Git link with no or very less activity will put a bad impression. Put in any other relevant links like your blog or website.Work Experience. This is the most crucial part and the core of your resume if you’re an experienced professional. Include the relevant work experience by making use of action verbs. Keep the points concise and don’t put in too much information. If you’re a fresher and don’t have any work experience, then add the relevant internship experience. If you don’t even have that, then skip this section and move to the next section and make that the core of your resume. Follow the writing style used in the template above. For checking how good your resume language is go to resumeworded.com.Personal Machine Learning Projects. This section should include 1 to 3 good machine learning projects that you’ve made recently. Write about them in short and include the most important details. Do not include beginner-level projects like the Titanic, House price prediction, etc. Adding these will not make your resume stand out. If you’re a fresher or if you don’t have any relevant work experience, then this section should be the core of your resume. Move it to the top and add enough content by making some very good projects.Skills. The skills section should include all the Machine Learning skills that you have- be it algorithms, tools and languages. A great way to make sure your resume clears the ATS is by adding the exact keywords mentioned in the JD of the job you’re applying for. This is because the ATS scores the resumes by the number of matches of keywords in the JD and your resume. So slightly alter the skills by replacing the words used in the JD. For example, Linear Regression should be changed to Linear Models, if the JD has that. Try to include as many keywords as possible, but do not include the ones you don’t know about.Hackathon Achievements. This is an additional section and can be skipped. You can also add another section that you’d want to show to the recruiter. Avoid adding your certifications from the MOOCs as they don’t add much weight to the resume. Only add certifications that would be relevant. Such as “Microsoft Certified Azure Specialist”, etc.Education. The education section should be kept at the bottom if you’re an experienced professional. If you’re fresh out of college, or still in college, you can keep it much above. This section should include the details only of your graduation- the degree, the college/university and the grade/CGPA earned. Dos and Don’ts of a Resume. Keep it on 1 pageInclude only relevant informationInclude keywords from the JDUse action words to describe the experienceRemove all the adjectivesAvoid including your photoBefore you go. We covered all the aspects of a great Machine Learning resume and how to maximize your chances of getting interview calls. The competition for the same job is a lot these days, but you can quickly skip the queue by working on the above point and making sure you don’t commit the same mistake others are committing. You can use this tutorial as a guide and build your resume from scratch. Just make sure not to just make one resume and use it for all the jobs. Instead, slightly alter it according to the job and the requirements. Just by doing these steps, you’re far ahead of the competition!If you’re interested to learn more about machine learning, check out IIIT-B & upGrad’s Executive PG Program in Machine Learning & AI which is designed for working professionals and offers 450+ hours of rigorous training, 30+ case studies & assignments, IIIT-B Alumni status, 5+ practical hands-on capstone projects & job assistance with top firms.What skills are required for Machine Learning? Machine Learning is a subset of Artificial Intelligence and its main application is in Data Mining or Pattern Recognition. It is very useful in developing automated decision-making systems. However, Machine Learning is not limited to that. Machine learning algorithms play an important role in natural language processing and data mining. Although it is an expertise, it should be considered a branch of computer science. Machine learning requires a good grasp on mathematics because it makes use of probability, statistics, and modeling. It is also important to have a strong background in computer programming languages like C, C++, Java, Python, Perl, C# .NET and R.How to build a good machine learning resume? Machine learning is a very hot field these days. If you want to build a machine learning resume, you will need to do some projects in the field. However, you can't just jump into the field without knowing anything about it. We will recommend you to do some pre-work before actually jumping into the machine learning field. You can design a curriculum for getting yourself ramped up for a machine learning role. The curriculum can start with a lot of math, but should go over the fundamentals you need to learn. After that, it should cover different concepts in machine learning. Then it should go over some more math.What is the future for machine learning? In recent years, we have seen a huge increase in the use of machine learning for effective business applications. Machine learning can be used for forecasting of customer behavior, recommending items to customers based on their history, making marketing more effective, etc. A study reported that 80% of businesses that use machine learning have experienced improved customer experience. Lead the AI Driven Technological Revolution. EXECUTIVE PG PROGRAM IN MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE APPLY NOWRelated Articles. Beginners Guide to Bayesian Inference: Complete Guide. by Pavan Vadapalli Nov 25, 2021 How to Perform Multiple Regression Analysis? by Pavan Vadapalli Nov 23, 2021 What is Probability Sampling? Definition, Methods. by Pavan Vadapalli Nov 22, 2021 Our Trending Machine Learning Courses. Advanced Certification in Machine Learning and Cloud from IIT Madras - Duration 12 Months Master of Science in Machine Learning & AI from IIIT-B & LJMU - Duration 18 Months Executive PG Program in Machine Learning and AI from IIIT-B - Duration 12 MonthsOur Popular Machine Learning Course. Related Articles. Beginners Guide to Bayesian Inference: Complete Guide. by Pavan Vadapalli Nov 25, 2021 How to Perform Multiple Regression Analysis? by Pavan Vadapalli Nov 23, 2021 What is Probability Sampling? Definition, Methods. by Pavan Vadapalli Nov 22, 2021 × × × × × Let’s do it!No, thanks.
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Result 15
TitleMachine Learning Resume NY - Hire IT People - We get IT done
Urlhttps://www.hireitpeople.com/resume-database/68-network-and-systems-administrators-resumes/147456-machine-learning-resume-ny
DescriptionI have 8+ years of work experience designing, building and implementing analytical and enterprise application using machine learning, Python, R, Scala,and Java.GoodExperience with a focus onBig data, Deep Learning, Machine Learning, Image processing or AI
Date
Organic Position15
H1
H2
H3Machine Learning Resume
H2WithAnchors
BodyWe provide IT Staff Augmentation Services! Machine Learning Resume . NY. Hire Now SUMMARY: I have 8+ years of work experience designing, building and implementing analytical and enterprise application using machine learning, Python, R, Scala,and Java. GoodExperience with a focus onBig data, Deep Learning, Machine Learning, Image processing or AI. Very good hands - on in Spark Core, Spark SQL, Spark Streaming and Spark machine learning using Scala and Python programming languages. Has very good experience implementing and handling end - to - end data science products. Good experience in periodic model validation and optimization workflows for the data science products developed. Good experience in extracting and analyzing the very large volume of data covering a wide range of information from a user profile to transaction history using machine learning tools. Collaborated with engineers to deploy successful models and algorithms into production environments. Good understanding of model validation processes and optimizations. An excellent understanding of both traditional statistical modeling and Machine Learning techniques and algorithms like Regression, clustering, ensembling (random forest, gradient boosting), deep learning (neural networks), etc. Proficient in understanding and analyzing business requirements, building predictive models, designing experiments, testing hypothesis, and interpreting statistical results into actionable insights and recommendations. Fluency in Python with working knowledge of ML & Statistical libraries (e.g. Scikit-learn, Pandas). Experience in processing real-timedata and building ML pipelines end to end. Very Strong in Python, statistical analysis, tools, and modeling. Very good hands-on experience working with large datasets and Deep Learning algorithms using apache spark and TensorFlow. An excellent understanding of both traditional statistical modeling and Machine Learning techniques and algorithms like Regression, clustering, ensembling (random forest, gradient boosting), deep learning (neural networks), etc. Good knowledge of recurrent neural networks, LSTM networks,and word2vec. Goodexperience in refining and improving our image recognition pipeline. Deep interest in learning both the theoretical and practical aspects of working with and deriving insights from data. Developed highly scalable classifiers and tools by leveraging machine learning, Apache spark & deep learning Worked under the direction of CSO to develop an effective solution to a predictive analytics problem, testing a number of potential machine learning algorithms of apachespark. Good experience in extracting and analyzingthe very large volume of data covering a wide range of information from a user profile to transaction history using machine learning tools. Built state-of-the-art statistical procedures, algorithms,and models to solve a range of problems in diverse domains. Proficient code writing capability in a major programming language such as Python, R, Java,and Scala. Good experience with deep learning frameworks like Caffe and TensorFlow. Experience using Deep Learning to solve problems in Image or Video analysis. Good understanding of Apache Spark features& advantages over map reduce or traditional systems. Very good hands-on in Spark Core, Spark SQL, Spark Streaming and Spark machine learning using Scala and Python programming languages. Solid Understanding of RDD Operations in Apache Sparki.e. Transformations & Actions, Persistence(Caching),Accumulators, Broadcast Variables. In-depth understanding of Apache spark job execution Components like DAG, lineage graph, Dag Scheduler, Task scheduler, Stages and task. Developed highly scalable classifiers and tools by leveraging machine learning, Apache spark & deeplearning. Highly organized and detail oriented, with a strong ability to coordinate and track multiple deliverables, tasks,and dependencies. Experience in exposing Apache Spark as web services. Worked under the direction of CSO to develop an effective solution to a predictive analytics problem, testing a number of potential machine learning algorithms of apache spark. Experience in real-time processing using Apache Spark and Kafka. Have good working experience of No SQL database like Cassandra and MongoDB. Delivered at multiple end-to-end Bigdata analytical based solutions and distributed systems like Apache Spark. Experience leveraging DevOps techniques and practices like Continuous Integration, Continuous Deployment, Test Automation, Build Automation and Test Hands on experience leading delivery through Agile methodologies Experience in managing code on GitHub Good hands on experience on Spring & Hibernate framework. Solid understanding of object-oriented programming. Familiarity with concepts of MVC, JDBC, and RESTful. Familiarity with build tools such as Maven and SBT. Knowledge of Information Extraction, NLP algorithms coupled with Deep Learning TECHNICAL SKILLS: Languages: Python,R,Scala,and Java Spark ML,Spark MLLib, Scikit: Learn. NLTK & Stanford NLP Deep learning framework: TensorFlow Big Data Frameworks: Apache Spark,Apache Hadoop, Kafka, Mongo DB,Cassandra. Machine learning: Linear regression, Logistic Regression, Naive Bayes, SVM, Decision Trees, Random Forest, Boosting, Kmeans,Bagging etc. Big data Distribution: Cloudera & Amazon EMRCloud Web Technologies: Flask,Django and spring MVC Front End Technologies: JSP, HTML5, Ajax, JQuery and XMLServers Web server: Apache2, Nginx Web Sphere,and Tomcat Visualization Tool: Apache Zeppelin, Matplotlib,and Tableau. Databases: Oracle, MySQL,and PostgreSQL. No SQL: MongoDB and Cassandra Operating Systems: Linux and windows Scheduling Tools: Airflow &oozie. PROFESSIONAL EXPERIENCE: Confidential Machine Learning Responsibilities: Converted data from PDF to XML using python script in two ways i.e. from raw xml to processed xml and from processed xml too.CSV files. Developing a generic script for the regulatory documents. Used python Element Tree(ET) to parse through the XML which is derived from PDF files. Data which is stored in sqlite3 datafile(DB.) were accessed using the python and extracted the metadata,tables,and data from tables and converted the tables to respective CSV tables. Used the XML tags and attributes to isolate headings,side-headings,and subheadings to each row in CSV file. Used Text Mining and NLP techniques find the sentiment about the organization. Deployed a spam detection model and performed sentiment analysis of customer product reviews using NLP techniques. Developed and implemented predictive models of user behavior data on websites, URL categorical, social network analysis, social mining and search content based on large-scale MachineLearning. Developed predictive models on large-scale datasets to address various business problems through leveraging advanced statistical modeling, machine learning,and deep learning. Extensively used Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn, SciPy and NLTK in R for developing various machine learning algorithms. Used R programming language for graphically critiquing the datasets and to gain insights to interpret the nature of the data. Researching on Deep Learning to implement NLP Clustering, NLP, Neural Networks. Visualized and presented the results using interactive dashboards. Involved in the transformation of files from GITHUB to DSX. Involved in the execution of CSV files in Data Science Experience. The major part is like being a part of the project, importing the converted CSV file to Confidential internal API which is InfoSphere Information Governance Catalog Used Beautiful Soup for web scraping (Parsing the data) Developed the code to capture the description which comes under headings of index section to the description column of CSV row. Used some other python libraries like PDFMiner, PyPDF2, PDFQuery, Sqlite3. Converted the uni-code to a nearest possible string (ASCII value) using Uni-decode module. Adding a column to each CSV row which gives the parent Index number of the given row. Environment: R Studio, AWS S3, NLP, EC2, Neural networks, SVM, Decision trees, MLbase, ad-hoc, MAHOUT, NoSQL, Pl/SQL, MDM, MLLib & Git. Confidential, NY Data Scientist Responsibilities: Performed data exploratory, data visualizations, and feature selections using Python and Apache Spark. Scaled Scikit-learn machine learning algorithms using apache spark. Using techniques such as Fast Fourier Transformations, Convolution Neural Networks,and Deep learning. I develop Deep Convolution and Recurrent Neural Networks with TensorFlow and have significant Risk Management & Quantitative Finance experience. Used multiplemachine learning algorithms, including random forest and boosted tree, SVM, SGD, neural network, and deep learning using TensorFlow. Used Python, Convolution Neural Networks (CNN), Deep Belief Networks (DBN), Theano, cafe etc. Applied unsupervised and supervised learning methods in analyzing high-dimensional data. Proficient use of Python Scikit-learn, pandas, and NumPy packages. Performed data modeling operations using Power Bi, Pandas, and SQL. Utilized Python libraries wxPython, NumPy, Twisted and matplotlib Used python libraries like Beautiful Soup and matplotlib. Developed and implemented predictive models of user behavior data on websites, URL categorical, social network analysis, social mining and search content based on large-scale Machine Learning, Wrote scripts in Python using Apache Spark and ElasticSearch engine for use in creating dashboards visualized in Grafana. Lead development for Natural Language Processing (NLP) initiatives with chat-bots and virtual assistants. Developed highly scalable classifiers and tools by leveraging machine learning, Apache spark & deep Converted Pandasdata frame dataset to apache spark data frame. Used multiple machine learning algorithms, including random forest and boosted tree, SVM, SGD, neural network, and deep learning using TensorFlow. Collaborated with engineers to deploy successful models and algorithms into production environments. Collaborated with a diverse team that includes statisticians, Chief Science Officer,and engineers to build data science project pipelines and algorithms to derive valuable insights from current and new datasets. Used PySparkdata frame to read text data,CSV data,Image data from HDFS, S3,andHive. Cleaned input text data using PySpark Machine learning feature exactions API. Created features to train algorithms. Used various algorithms of PySparkMLAPI. Trained model using historical data stored in HDFS and Amazon S3. Used Spark streaming to load the trained model to predict real-time data from Kafka. Stored the result in MongoDB. Utilized various new supervised and unsupervised machine learning algorithms/software to perform NLP tasks and compare performances The web application can pick data which is stored in MongoDB. Used Apache Zeppelin to visualization of Big Data. Fully automated job scheduling, monitoring, and cluster management without human interventionusing airflow. Build apache spark as Web service using a flask. worked with input file formats like an orc, parquet, Json, Avro. Developed highly scalable classifiers and tools by leveraging machine learning, Apache spark & deep learning. Wrote Spark SQL UDFs, Hive UDFs. Optimized Spark coding suing Performance Tuning of apache spark. Optimized machine learning algorithms based on need. Used amazon elastic MapReduce (EMR) to process a hugenumber of datasets using Apache spark and TensorFlow. Environment: Machine learning, Scikit-learning,Pandas, Spark core, Spark SQL, Spark streaming, Python, airflow,Amazon EMR, ec2, s3,pandas,NumPy,matplotlib, TensorFlow,Kafka,flask,MongoDB,Hive, HDFS,GitHub, REST & airflow. Confidential - Columbus, OH Data Scientist Responsibilities: Collaborated with internal stakeholders to understand business challenges and develop analytical solutions to optimize business processes. Performed analysis using industry leading text mining, data mining, and analytical tools and open source software. Used MATLAB, C/C++ with OpenCV and SVM, Neural Networks, Random Forest as classifiers. Generated graphical reports using python package NumPy and matplotlib. Built various graphs for business decision making using Pythonmatplotlib library. Knowledge of Information Extraction, NLP algorithms coupled with Deep Learning (ANN and CNN), Theano, Keras,andTensorFlow. Built and trained a deep learning network using TensorFlow on the data, and reduced wafer scrap by 15%, by predicting the likelihood of wafer damage. A combination of the z-plot features, image features (pigmentation) and probe features are being used. Experienced in ArtificialNeuralNetworks(ANN) and DeepLearning models using Theano, TensorFlow and Keras packages using Python. Used Natural Language Processing (NLP) to pre-process the data, determine the number of words and topics in the emails and form cluster of words Cleaned input text data using PySparkMachine learning feature exactions API. Used Pandas data frame for exploratory data analysis on sample dataset. Wrote Scikit learn based machine learning algorithms for building POC’s on sample dataset. Analyzedstructured, semi-structured and unstructured dataset using map-reduce and apache spark. Implemented end to end lambda architecture to analyze streaming and batch dataset. Used Apache Mahout’s scalable machine learning algorithms for building recommendation engine, for building classification and regression model. Converted mahout’s machine learning algorithms to RDD based ApacheSparkMLLib to improve performance. Optimizedmachine learning algorithms based on need. Automatic music/news/POI recommendation inside the vehicle by using GPS location, passenger conversation, behavior,and mood. Using machine learning and natural language. Smart state-of-charge monitor for electric vehicles based on RecurrentNeuralNetwork and Seq2Seq forecast. Build multiple features of machine learning using python, Scala,andJava based on need. Developed multiple MapReduce jobs in java for data cleaning and preprocessing. Migrated single machine learning machine learning algorithms to Parallel processing algorithms. Developed Hive queries for ad-hoc analysis. Used amazon elastic MapReduce (EMR) to process a hugenumber of datasets using Apache spark and TensorFlow. Lead Data Scientist for development of Machine Learning and NLP engines utilizing health population Data. Analyzed the partitioned and bucketed data and compute various metrics for reporting. Involved in loading data from RDBMS and weblogs into HDFS using Sqoop and Flume Involved in building complex streaming data Pipeline using Kafka and Apache Spark. Worked on loading the data from MySQL to HBase where necessary using Sqoop. Exported the result set from Hive to MySQL using Sqoop after processing the data. Optimized hive queries. Optimized MapReduce and apache spark jobs. Wrote custom input formats in map reduce to analyses image dataset. Wrote Hive UDF’s based on need. Environment: Hadoop, Map Reduce, Hive, Mahout, Apache Spark, Python, Scikit learn, Pandas, NumPy, Java, Maven, Eclipse, MySQL, Kafka,Sqoop & Flume. Confidential, NY Data Scientist Responsibilities: Responsible for performing Machine-learning techniques regression/classification to predict the outcomes. Responsible for design and development of advanced R/Python programs to prepare to transform and harmonize data sets in preparation for modeling. Designed and automated the process of score cuts that achieve increased close and good rates using advanced R programming. Utilized Convolution Neural Networks to implement a machinelearning image recognition component. Managed datasets using Panda data frames and MySQL, queried MYSQL relational database(RDBMS) queries from python using Python-MySQL connector MySQL dB package to retrieve information. Utilized standard Python modules such as csv, itertools,and pickle for development. Tech stack is Python 2.7/PyCharm/Anaconda/pandas/NumPy/unittest/R/Oracle. Developed large data sets from structured and unstructured data. Perform data mining. Partnered with modelers to develop data frame requirements for projects. Performed Ad-hoc reporting/customer profiling, segmentation using R/Python. Tracked various campaigns, generating customer profiling analysis and data manipulation. Provided python programming, with detailed direction, in the execution of data analysis that contributed to the final project deliverables. Responsible for data mining. Analyzed large datasets to answer business questions by generating reports and outcome. Worked with a team of programmers and data analysts to develop insightful deliverables that support data-driven marketing strategies. Executed SQL queries from R/Python on complex table configurations. Retrieving data from the database through SQL as per business requirements. Create, maintain, modify and optimize SQL Server databases. Manipulation of Data using python Programming. Adhering to best practices for project support and documentation. Understanding the business problem, build the hypothesis and validate the same using the data. Managing the Reporting/Dashboarding for the Keymetrics of the business. Involved in data analysis using different analytic techniques and modeling techniques. Environment: Python,Oracle,Python, Scikit learn,Pandas, NumPy, SciPy, NLTK,Jupyter notebook,R,and Studio Confidential Data Analyst/Data Modeler Responsibilities: Developed end to end enterprise Applications using Spring MVC, REST and JDBC Template Modules. Written well designed testable, efficient java code. Understanding and analyzing complex issues and addressing challenges arising during the software development process, both conceptually and technically. Implemented best practices of Automated Build, Test and Deployment. Developed design patterns, data structures,and algorithms based on project need. Worked on multiple tools such as Toad, Eclipse, SVN, Apache,andTomcat. Deployed models via APIs into applications or workflows Worked on User Interface technologies like HTML5, CSS/SCSS. Wrote Stored procedure and SQL queries based on project need. Deployed built jar into the application server. Created Automated Unit Tests using Flexible/Open Source Frameworks Developed Multi-threaded and Transaction Handling code (JMS, Database). Environment: Java, Spring MVC, Hibernate, JMS, HTML5, CSS/SCSS, Junit, Eclipse, Tomcat,and Oracle. 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Topics
  • Topic
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  • Position
  • data
  • 62
  • 15
  • learning
  • 56
  • 15
  • spark
  • 39
  • 15
  • machine
  • 36
  • 15
  • machine learning
  • 35
  • 15
  • python
  • 29
  • 15
  • apache
  • 28
  • 15
  • algorithm
  • 25
  • 15
  • apache spark
  • 23
  • 15
  • deep
  • 21
  • 15
  • experience
  • 20
  • 15
  • deep learning
  • 17
  • 15
  • model
  • 15
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  • developed
  • 15
  • 15
  • network
  • 15
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  • learning algorithm
  • 14
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  • good
  • 14
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  • dataset
  • 14
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  • end
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  • based
  • 13
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  • tool
  • 12
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  • neural
  • 12
  • 15
  • nlp
  • 12
  • 15
  • neural network
  • 11
  • 15
  • sql
  • 11
  • 15
  • analysi
  • 11
  • 15
  • machine learning algorithm
  • 10
  • 15
  • understanding
  • 10
  • 15
  • tensorflow
  • 10
  • 15
  • technique
  • 9
  • 15
  • business
  • 9
  • 15
  • scikit
  • 9
  • 15
  • feature
  • 9
  • 15
  • language
  • 8
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  • large
  • 8
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  • project
  • 8
  • 15
  • scikit learn
  • 7
  • 15
  • good hand
  • 6
  • 15
  • random forest
  • 6
  • 15
  • programming language
  • 5
  • 15
  • end end
  • 5
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  • good experience
  • 5
  • 15
  • developed highly scalable
  • 4
  • 15
  • highly scalable classifier
  • 4
  • 15
  • scalable classifier tool
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  • classifier tool leveraging
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  • tool leveraging machine
  • 4
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  • leveraging machine learning
  • 4
  • 15
  • machine learning apache
  • 4
  • 15
  • learning apache spark
  • 4
  • 15
  • spark core
  • 4
  • 15
  • spark sql
  • 4
  • 15
  • spark streaming
  • 4
  • 15
  • python programming
  • 4
  • 15
  • data science
  • 4
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  • predictive model
  • 4
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  • developed highly
  • 4
  • 15
  • highly scalable
  • 4
  • 15
  • scalable classifier
  • 4
  • 15
  • classifier tool
  • 4
  • 15
  • tool leveraging
  • 4
  • 15
  • leveraging machine
  • 4
  • 15
  • learning apache
  • 4
  • 15
  • map reduce
  • 4
  • 15
  • data scientist
  • 4
  • 15
  • dataset apache
  • 4
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  • data frame
  • 4
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  • visa sponsorship
  • 4
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  • spark core spark
  • 3
  • 15
  • core spark sql
  • 3
  • 15
  • spark sql spark
  • 3
  • 15
  • sql spark streaming
  • 3
  • 15
  • statistical modeling machine
  • 3
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  • machine learning technique
  • 3
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  • scikit learn panda
  • 3
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  • learning algorithm apache
  • 3
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  • algorithm apache spark
  • 3
  • 15
  • apache spark tensorflow
  • 3
  • 15
  • apache spark deep
  • 3
  • 15
  • data scientist responsibility
  • 3
  • 15
  • dataset apache spark
  • 3
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  • core spark
  • 3
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  • sql spark
  • 3
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  • statistical modeling
  • 3
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  • modeling machine
  • 3
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  • learning technique
  • 3
  • 15
  • learn panda
  • 3
  • 15
  • algorithm apache
  • 3
  • 15
  • spark tensorflow
  • 3
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  • spark deep
  • 3
  • 15
  • big data
  • 3
  • 15
  • spring mvc
  • 3
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  • data stored
  • 3
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  • csv file
  • 3
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  • large scale
  • 3
  • 15
  • panda numpy
  • 3
  • 15
  • python library
  • 3
  • 15
  • ad hoc
  • 3
  • 15
  • scientist responsibility
  • 3
  • 15
  • convolution neural
  • 3
  • 15
  • natural language
  • 3
  • 15
  • algorithm based
  • 3
  • 15
  • data mining
  • 3
  • 15
  • data analysi
  • 3
  • 15
Result 16
TitleResume | Emilien Dupont
Urlhttps://emiliendupont.github.io/resume/
DescriptionMachine Learning
Date
Organic Position16
H1Resume
H2Education 🎓
Experience 👨‍💼
Awards 🌟
Teaching 👨‍🏫
Skills 💻
Projects 🌱
Academic Services 📚
Invited Talks 🏛️
H3
H2WithAnchorsEducation 🎓
Experience 👨‍💼
Awards 🌟
Teaching 👨‍🏫
Skills 💻
Projects 🌱
Academic Services 📚
Invited Talks 🏛️
BodyResume For more details, you can download the pdf version of my resume pdf here (updated December 2021). Education 🎓. University of Oxford 2018 - PhD Machine Learning Supervised by Yee Whye Teh and Arnaud Doucet Stanford University 2014 - 2016 MS Computational Mathematics GPA: 4.02 Imperial College London 2010 - 2014 BSc Theoretical Physics Rank: 1/206 students, Grade: 87.2% Experience 👨‍💼. Google DeepMind Mar 2021 - July 2021 Research Scientist Intern Research with Danilo Rezende Apple Nov 2019 - June 2020 Part Time Research Intern Part time research on neural rendering during PhD with collaborators at Apple Apple June 2019 - Aug 2019 Research Intern Research on Neural Rendering with Qi Shan Schlumberger STIC June 2016 - July 2018 Machine Learning Scientist Created, implemented and deployed machine learning algorithms to solve problems in time series, vision and geology, improving state of the art for several tasks • Research on deep generative models with a focus on learning interpretable representations Gurobi Optimization June 2015 - Aug 2015 Software Engineering Intern Researched, formulated and solved integer optimization models for a wide area of industry applications including energy, telecom and medicine DTU Compute June 2013 - Sep 2013 Research Intern Research on sparse dynamics for PDEs with Allan Engsig-Karup Awards 🌟. Google DeepMind Scholarship 2018 PhD funding, 150,000 USD Schlumberger Out of the Ordinary Award 2018 Award for extraordinary technical achievements Digital Forum Innovation Award 2017 Schlumberger award for most innovative project among 300+ submissions Schlumberger AI Leader 2016 Elected as leader of the 1000+ AI community within Schlumberger Governor's Prize 2014 Ranked 1st of 206 students in Physics at Imperial College London Teaching 👨‍🏫. Teaching Assistant, SB2.1, Statistical Inference Oxford, 2020 Teaching Assistant, SB2.2, Statistical Machine Learning Oxford, 2019 Teaching Assistant, CME 102, Ordinary Differential Equations Stanford, 2016 Skills 💻. Programming Experienced: Python, C++, Matlab Familiar: Javascript, Scala (Spark) Frameworks Deep Learning: Pytorch, Jax, Haiku, Keras Visualization: d3, plotly Languages Fluent: Danish, English, French Intermediate: German Projects 🌱. Visualizations Created d3 based interactive visualizations of mathematical concepts, data and generative art, which can be found on my Observable profile Open source Open sourced code for several deep learning papers with ★1000+ on my Github profile Academic Services 📚. Reviewer AISTATS 2022, ICLR 2022, ICLR 2021 (Outstanding reviewer), NeurIPS 2020 (Outstanding reviewer), ICML 2020 (Top reviewer), NeurIPS 2019 (Top reviewer) Invited Talks 🏛️. The Curse of Discretization and Learning Distributions of Functions 2021 ML Collective Representational Limitations of Invertible Models 2020 ICML 2020, INNF+ Workshop Combining Physics and Machine Learning with Neural ODEs 2019 Abingdon, UK Deep Learning for Prognostics and Health Management Tutorial 2017 Prognostics and Health Management Conference, Tampa Bay, FL Deep Learning Applications Panel 2017 Prognostics and Health Management Conference, Tampa Bay, FL
Topics
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  • Tf
  • Position
  • learning
  • 11
  • 16
  • research
  • 9
  • 16
  • 2019
  • 6
  • 16
  • 2020
  • 6
  • 16
  • machine learning
  • 5
  • 16
  • 2021
  • 5
  • 16
  • machine
  • 5
  • 16
  • intern
  • 5
  • 16
  • june
  • 5
  • 16
  • schlumberger
  • 5
  • 16
  • deep
  • 5
  • 16
  • award
  • 5
  • 16
  • reviewer
  • 5
  • 16
  • deep learning
  • 4
  • 16
  • 2018
  • 4
  • 16
  • 2016
  • 4
  • 16
  • teaching
  • 4
  • 16
  • prognostic health management
  • 3
  • 16
  • intern research
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  • 16
  • research intern
  • 3
  • 16
  • teaching assistant
  • 3
  • 16
  • prognostic health
  • 3
  • 16
  • health management
  • 3
  • 16
  • oxford
  • 3
  • 16
  • phd
  • 3
  • 16
  • 2014
  • 3
  • 16
  • physic
  • 3
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  • apple
  • 3
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  • time
  • 3
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  • neural
  • 3
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  • model
  • 3
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  • 2017
  • 3
  • 16
  • assistant
  • 3
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  • visualization
  • 3
  • 16
  • prognostic
  • 3
  • 16
  • health
  • 3
  • 16
  • management
  • 3
  • 16
Result 17
Title
Urlhttps://www.resumecompass.co/resume-examples/machine-learning-engineer-resume-sample
Description
Date
Organic Position17
H1
H2
H3
H2WithAnchors
Bodyable JavaScript to run this web app.
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Result 18
TitleMachine Learning Engineer Resume Writer & Template | Rocket Resume
Urlhttps://rocket-resume.com/resumes/misc/machine-learning-engineer-perfect-resume-writer-templates
DescriptionUse Rocket Resume's machine learning engineer resume writer. Write your resume now with the perfect recruiter-approved resumes & templates. Get hired faster with Rocket Resume!
Date
Organic Position18
H1Machine Learning Engineer Resume Writer & Template
H2Use this Machine Learning Engineer resume to start your own
Rocket Resume helps you get hired faster
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H3Use Rocket Resume's machine learning engineer resume writer. Write your resume now with these recruiter-approved resumes & template
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Rocket Resume helps you get hired faster
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BodyMachine Learning Engineer Resume Writer & TemplateUse Rocket Resume's machine learning engineer resume writer. Write your resume now with these recruiter-approved resumes & template.Write Resume NowUse this Machine Learning Engineer resume to start your own. Start with this template to write the perfect resume, we'll help you along the wayRocket Resume helps you get hired faster. Everything you need to build your resume, in one place10 minutes to build your resumeOur smart tools make building a polished resume faster, so you can concentrate on landing that dream jobUse recruiter-approved bullet pointsWe'll suggest pre-written industry-specific text specifically aligned to every section of your resumeBuild your resume, get hired fasterDownload your resume and share it directly with hiring managersOver 2 million resume templatesGrab an existing template for your industry, or customize one so its just right for youBuild Resume NowMachine Learning Engineer resumes. Use these Machine Learning Engineer to easily write your resume more perfectlyPreviousNextReady to start building your resume?How much experience do you have? We'll offer custom-tailored recommendations to help you build the fast resumeNo ExperienceLess Than 3 Years3-5 Years5-8 Years8+ YearsBuild Resume NowMachine learning engineer resume templates. Save these templates to write your ownBuild Machine Learning Engineer ResumeMachine learning engineer resumes and templates. Choose an existing template or write your own using Rocket Resume's advanced resume editorSee more resume templatesOther miscellaneous resumes and template. Search our resumes and use them to write your ownWrite Miscellaneous Resume NowRelated resumes and template. Search our resumes and use them to write your ownWrite Resume NowWrite your resume more perfectly with Rocket Resume. Search our resumes and use them to write your ownWrite Resume NowSearch and browse resume templates. Use these resumes and our free templatesAcademia ResumesAccounting and Finance ResumesAdvertising ResumesAerospace ResumesAgriculture and Ranching ResumesAirline ResumesArchitecture ResumesArt and Design ResumesAutomotive and Motor Vehicles ResumesBanking and Financial Services ResumesBeauty and Spa ResumesBiotechnology ResumesChemicals ResumesChildcare ResumesCommunity and Public Service ResumesComputers Hardware ResumesComputers Networking and Security ResumesComputers Software ResumesConstruction ResumesCustomer Service ResumesDental ResumesEducation and Training ResumesElectronics ResumesEmergency Services ResumesEnergy and Utilities ResumesEntertainment and Performing Arts ResumesFitness and Recreation ResumesFood and Beverage ResumesForestry and Natural Resources ResumesGardening and Horticulture ResumesGovernment ResumesGraphic Design and Animation ResumesHealthcare ResumesHuman Resources ResumesInformation Technology ResumesInsurance ResumesLaw Enforcement and Security ResumesLegal ResumesLibrary ResumesManufacturing and Production ResumesMarketing and Communications ResumesMedia and Journalism ResumesMedical Devices ResumesMental Health ResumesMilitary ResumesMining and Extraction ResumesMiscellaneous ResumesPharmacy ResumesPublic Relations ResumesPublishing ResumesReal Estate ResumesRetail ResumesShipping and Distribution ResumesSports ResumesTelecommunications and Wireless ResumesTextile and Apparel ResumesTransportation ResumesTravel and Hospitality ResumesVeterinary ResumesWarehousing ResumesBrowse more resumes
Topics
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  • resume
  • 36
  • 18
  • template
  • 9
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  • learning engineer
  • 8
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  • learning
  • 8
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  • engineer
  • 8
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  • 8
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  • 7
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  • learning engineer resume
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  • engineer resume
  • 6
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  • machine learning engineer
  • 5
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  • machine learning
  • 5
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  • resume template
  • 5
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  • machine
  • 5
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  • service
  • 4
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  • search resume write
  • 3
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  • resume write ownwrite
  • 3
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  • rocket resume
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  • template write
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  • resume write
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  • resumescomputer
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Result 19
TitleMachine Learning Resume Sample | MintResume
Urlhttps://www.mintresume.com/resumes/machine-learning
DescriptionAnalytical thinking skills, with demonstrated ability to dive deep into quantitative and qualitative data to solve problems and improve customer experience ...
Date
Organic Position19
H1
H2
H3
H2WithAnchors
Body
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Result 20
TitleCV
Urlhttps://dcorney.com/CV/
Description
Date
Organic Position20
H1David Corney
H2CV
David Corney, PhD
H3
H2WithAnchorsCV
David Corney, PhD
BodyDavid Corney CV. David Corney, PhD. Profile I am a Data Scientist and Engineer with a proven track record in applying ahead of the curve technologies to solve data-driven problems including: extracting information from biomedical publications to aid drug discovery; collecting and analysing tweets in real-time to help journalists track breaking stories; and analysing large volumes of news articles for a media monitoring tool. With many years experience of applying machine learning and natural language processing to solve real-world problems both in industry and academia, I am always interested in new opportunities in organisations that will allow me to continue to apply and extend my expertise by exploring new areas. Professional Experience Full Fact    February 2019 - present Lead NLP Engineer I lead the application of machine learning and NLP techniques to help fact checkers work more effectively. This includes developed a “claim type” classifier, that models whether a sentence contains a prediction, or a personal believe, or a quantitative claim. The latter are often easier to check, so this can help fact checkers to select claims to check more quickly. I’ve also worked on a fully-automated “robochecking” tool, though this remains a working prototype. Dunnhumby    April 2018 - February 2019 Senior Data Scientist I helped develop a fine-grained sales prediction model, predicting sales levels of individual items at a daily level for individual stores. My work included developing high performance Python code, capable of making millions of forecasts quickly. Factmata    January 2018 - April 2018 Lead Machine Learning/NLP Engineer I developed a prototype “fake news” detector as well as running several pilot studies with adtech companies. I was also involved with supervising more junior staff, recruitment, external collaborations and co-organizing the Hyperpartisan News Detection Challenge, part of Semeval19. Signal Media Ltd    September 2014 - December 2017 Data Scientist My role was to discover, evaluate and apply the latest research in natural language processing (NLP) and machine learning to analyse and classify news articles at a large scale in real-time. Working in agile teams, our aim is to develop prototypes based on current research with production-quality code and turn them into products. Leading the development of novel AI components and proofs-of-concept including a novel entity recognition system, a topic classification system and a horizon-scanning / sentiment analysis tool. Managed a number of key 3-6 month projects with multinational clients, working closely with external stakeholders to understand the brief, communicating their requirements to engineering colleagues and demonstrating progress throughout the projects through reports and presentations. Maintaining and strengthening Signal’s links to the academic and research communities. Outreach includes presenting work at WSDM and Search Solutions; giving regular guest lectures at City University. Hosted, mentored and supervised 7 MSc Data Science and Machine Learning students during projects by providing technical guidance and advice for their data science work, which formed the basis of new product features at signal. Two students went on to study PhDs and two joined Deepmind. Led interactive sessions on the basics of AI/machine learning to all staff with a view to bridging the gap between technical and non-technical teams. Analysed and indexed regulation documents collected from several jurisdictions. This work included entity and topic recognition using machine learning as well as several specialist modules to aid user’s in their search tasks. Each piece of work included either statistical data-driven evaluation or a user-centred evaluation stage. Bring the benefits of rapid scalability to the components I develop for Signal’s platform by using Amazon’s cloud computing system (such as the EC2 and S3 features), whilst controlling costs. Technologies used include: Python, Clojure, ElasticSearch, AWS, GitHub, NLTK, spaCy and scikit-learn. Robert Gordon University & City University London     April 2012-September 2014 Senior Research Fellow My role was to work with journalists and developers to build tools to find and organise real-time news from Twitter. Worked closely with journalists from City University and elsewhere to understand their needs. I developed methods and algorithms to help journalists find breaking news stories from Twitter through novel trend-detection and ‘news-hound’ discovery methods. Co-organized the SNOW workshop data challenge, where I led the evaluation of 10 international teams’’ submissions to a news-detection task. Acted as bridge between software engineering colleagues and journalist colleagues, translating each others needs into terms the others could understand more easily. Lead author of quarterly & annual reports to our key stakeholder (the European Commission), which included coordinating with partners from several organisations across Europe. Technologies used include: Java, R, MongoDB, Twitter APIs. Department of Computing, University of Surrey     2009-2012 Research Fellow My role was to develop innovative tools to analyse pictures of plant specimens from Kew Gardens to aid species identification and understand the effects of climate change. Developed image processing software to extract botanical characteristics from images of herbarium leaf specimens stored at Kew Gardens. Developed a machine learning system that could assign species labels to these images. Created a proof-of-concept system which required me to rapidly develop skills in both botany and image processing. Defined and collected a unique set of data to help develop and evaluate the system Technologies used include: Matlab, Java. University of Hertfordshire     2008-2011 Part-time visiting lecturer My responsibilities include online supervision of undergraduate honours degree students, including marking coursework and exams. Institute of Ophthalmology, UCL     2006-2009 Research fellow My role was to improve understanding of visual perception through computer modelling and data analysis. Investigated human and insect vision in collaboration with visual and computational neuroscientists Used statistical and machine learning tools such as neural networks, to produce “virtual animals” that learned to interpret simple scenes within a synthetic ecology Demonstrated likely evolutionary origins of optical illusions Queen Mary, University of London    2004-2006 Part-time distance learning tutor Responsible for the online supervision of undergraduate honours degree students, including marking coursework and exams. University College, London, Department of Computer Science    2001-2006 Senior Research Fellow Worked with pharmaceutical researchers and developed tools to automatically extract information from research papers. I developed software (BioRAT) designed to locate research papers on the internet and to extract useful information from them to build a database. Helped develop a machine learning algorithm to discover novel patterns of information in unstructured text using NLP. Worked with a major pharmaceutical company to assist their drug-development programs. Worked with medical and pharmaceutical researchers and with information architects to understand their needs. Regularly presented work to senior managers, including budget holders. Technologies used include: Java, GATE. UCL     April-September 1999 Part-time research consultant During the my PhD, I was employed as a research consultant on a project bringing together retailers and academics to investigate targeted advertising for home shoppers. My work included the evaluation of several data mining tools and an initial set of data mining studies. Co-authored several reports and presentations to the partners. Fraser Williams plc    1995-1997 Analyst Programmer London software house where I was involved in designing and programming large-scale database systems. These involved long-term projects for clients drawn from both the public and private sectors. Visited clients on-site to discuss and clarify their needs, and to provide training Supervised junior programmers and provided on-the-job training. Technologies used include: PRO-IV, SQL, VB. Education PhD Computer Science at University College London    1998-2002 My thesis title was “Intelligent Analysis of Small Data Sets for Food Design”, and concerned the development and evaluation of machine learning methods, motivated by product design work within the food industry. The aim was to model consumer preferences of food products by learning relationships from very small data sets. Areas researched include feature selection, cluster analysis, outlier detection, regression, and Bayesian belief networks. Unilever plc sponsored this work and provided data and advice throughout. I spent 6 months at one of their research centres, which allowed me to disseminate current academic thinking within Unilever and learn more about their approaches to data analysis. MSc Computational Intelligence (with Distinction) at Plymouth University    1997-1998 This included study of adaptive intelligent systems such as genetic algorithms and neural networks, and their application to engineering, business and financial systems. My project work investigated the use of “genetic programming” for modelling consumer laundry datasets provided by Unilever plc. BSc (Hons.) Cognitive Science, Class 2 (ii) from Exeter University     1991-1994 This included study of artificial intelligence, neural networks, perception, cognition and linguistics, along with more general computer science and psychology modules. Skills and Experiences Computing Skills I have professional experience of several major programming languages and databases, including Python, Clojure, Matlab, Java, ElasticSearch and MongoDB, along with exposure to R, C++, VB, Prolog, SQL and PRO-IV. I have also used major libraries such as scikit-learn, NLTK, spaCy, GATE and tools including GitHub and AWS. For much of this work, I have been a member of agile and cross-functional teams including developers, designers and end-users. Hobbies Keeping fit is an important part of my life and I enjoy running, regularly competing in 10k races. For two years, I served as the treasurer for a local tenants and residents association, helping to track expenses and plan spending on several community projects. Recently, I’ve become skilled in woodwork, making children’s toys, decorations and several small items of furniture. Selected Publications A full set of my peer-reviewed publications is available online at dcorney.com/publications, and copies of all papers are available on request. Recent papers include: D. Corney, D. Albakour, M. Martinez and S. Moussa (2016) “What do a Million News Articles Look Like?” in First International Workshop on Recent Trends in News Information Retrieval (NewsIR’16; co-located with ECIR 2016), Padua, Italy. Full text S. Schifferes, N. Newman, N. Thurman, D. Corney, A. Göker, and C. Martin, (2014) “Identifying and verifying news through social media,” Digital Journalism 2(3), pp. 406-418. E. Byrne and D. Corney (2014) “Sweet FA: sentiment, swearing and soccer,” in ICMR2014 1st Workshop on Social Multimedia and Storytelling, Glasgow, UK, Apr. 2014. Pre-print. Aiello, L.M., Petkos,G., Martin, C., Corney, D.P.A., Papadopoulos, S., Skraba, R., Goker, A., Kompatsiaris,Y., Jaimes A. (2013) “Sensing trending topics in Twitter”, IEEE Transactions on Multimedia. DOI: dx.doi.org/10.1109/TMM.2013.2265080
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Result 21
TitleMachine Learning Engineer Resume Samples and Guide
Urlhttps://www.resumecoach.com/resume-samples/machine-learning-engineer/
DescriptionDesign and build the perfect machine learning engineer resume to get you in contention for the next step up in your career in data science and management
Date
Organic Position21
H1Machine Learning Engineer Resume Examples
H2Professional Resume Samples for Machine Learning Engineer
Resume Samples
Machine Learning Engineer Resume Vocabulary & Writing Tips
Machine Learning Engineer Resume Tips and Ideas
Machine Learning Engineer Resume Section Headings
Related Samples
H3Samples Resume
Samples Resume
Words to Use
Action Verbs
Format
Design
Photo
Sections of a Machine Learning Engineer Resume
Work experience
Skills
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H2WithAnchorsProfessional Resume Samples for Machine Learning Engineer
Resume Samples
Machine Learning Engineer Resume Vocabulary & Writing Tips
Machine Learning Engineer Resume Tips and Ideas
Machine Learning Engineer Resume Section Headings
Related Samples
BodyMachine Learning Engineer Resume Examples Take your machine learning engineer resume to new levels with professional tips and tricks Upgrade your resume Format Recommended: Reverse-chronologicalOptional: Combination Design Write in a consistent and legible fontDesign a clean and organized templateBreak up long paragraphs into bullet pointsCreate clear, easy to find sectionsSave your file as a PDF Resume Length 1-2 x letter pages (8.5” x 11”) Professional Resume Samples for Machine Learning Engineer . Use this template Use this template Use this template Use this template Use this template Use this template Use this template Use this template Use this template Use this template View more examples View less examples Written by RC Team Author Updated on November 30th, 2021 Resume Samples . 1. Candidate seeking a Machine Learning Engineer role: Samples Resume. Copy to clipboard Resume summary statement: Data-driven Machine Learning Engineer, fully proficient in C++ and Python with a problem-solving mindset, analytical approach to tasks and strong knowledge of financial sector necessities.Developed advanced machine learning systems adapted to the finance industry best practicesCollaborated with key project stakeholders to ensure that essential goals were metCreated effective databases that assisted in project planning and new product launchesResearched and tested new technologies to support the growth of the business and to maintain competitiveness 2. Candidate seeking a Machine Learning Engineer role: Samples Resume. Copy to clipboard Resume summary statement: Motivated Machine Learning Engineer with an in-depth knowledge of designing and maintaining MySQL systems and optimizing algorithms for the best performance possible.Optimized database performance by fine-tuning operational functionsDeveloped effective and advanced back-end machine learning programsAdjusted systems to improve dataset usability, scalability and distribution systemsMentored 5 new members of data-science staff and assisted in the training of employees in database management Machine Learning Engineer Resume Vocabulary & Writing Tips . The words you squeeze onto the page should be carefully chosen. You should aim to get a good quantity of sector-specific vocabulary onto the page. This doesn’t need to be too technically in-depth, but it should show you know the job like the back of your hand.This is equally important due to the increase in the use of ATS tools. These will penalize resumes that don’t make enough use of these keywords as well as documents that contain spelling or grammatical errors. Words to Use. Dependencies Continuous integration Software development Algorithm Machine learning algorithm Deployment Architectures Security scenarios .NET Linear regression A/B tests Performant systems Applied statistics Lane-finding Deep learning Data structures Action Verbs. Create Test Research Prepare Deploy Analyze Debug Write Code Operate Troubleshoot Manage Program Design Measure Build Machine Learning Engineer Resume Tips and Ideas . Does your machine learning engineer resume have the right stuff to succeed?This is an ever-expanding profession, with company data-management needs increasing exponentially each year. However, going into a job opening with an optimized resume can still often make the difference.There’s a lot that needs to be included in a professional profile like this. Employers will want to see a mix of programming skills, system management experience, and algorithm optimization amongst other things. Therefore, how you design and fill your document counts!To make this all a little easier, the following guide explains the best ways to optimize your resume for a machine learning engineer opening. It will take you through the most effective ways to design, structure and fill in your document so that it gets results. To save even more time and create a resume that’s ready to perform, simply use these tips with our professional resume generator. Format Recommended: Reverse-chronologicalOptional: Combination Design Write in a consistent and legible fontDesign a clean and organized templateBreak up long paragraphs into bullet pointsCreate clear, easy to find sectionsSave your file as a PDF Photo No Sections Required: Contact information Resume summary statement Work experience Skills Education Optional: Projects Certifications and courses Hobbies and interests Resume Length 1-2 x letter pages (8.5” x 11”) Format . There are a couple of options available to machine learning engineers when it comes to resume formats. Your biggest selling points are your experience and your skills. These can be emphasized on the page with one of the two following formats.The first of these, and the most common resume format used today is a reverse-chronological design. This promotes your work experience above all other considerations and is the absolute best choice for experienced candidates.In the case of the candidates moving into the profession from study or a career in another sector, it’s much better to focus on your transferable skills as well as relevant work experience. To achieve this it can sometimes be better to use a combination format resume. This places equal emphasis on both your abilities and your work history and could help if your work experience section is a little more sparse in terms of recent data science roles. Design . Designing a well-optimized resume can sometimes feel a little intricate. There are a lot of little tips and tricks that can make a difference during this step and fortunately, very few of them are complicated or hard to implement.One of the first things to do when planning the layout is to not overfill the document with information. Leave a little white space available to separate out sections and really let the details on the page stand out. Ideally, the sections themselves should be well-marked and easy to identify.Avoid the temptation of adding fancy embellishing features like graphics, elaborate borders, and custom fonts. These could undermine your professionality and will most likely deoptimize your resume for Applicant Tracking Software (ATS).When you write the information into the structure you’ve laid out, use a consistent and easily legible font. The most important thing your resume can do is communicate a lot of information fast and by making the writing easily legible you’ll do this much more effectively. This can also be made much easier by breaking up longer texts into easy to skim-read bullet points. Photo . In most cases, a photo isn’t required on a machine learning engineer resume. Employers in the UK, US and Canada do not expect this, nor make it a pre-requisite due to strict employment discrimination laws. However, adding a photo to your resume is often needed in countries like France, Germany or Spain. Therefore, if you’re applying for a position in one of these job-markets a professional picture should be included. Sections of a Machine Learning Engineer Resume . To organize all the relevant information on the page you need to break up your details into clear and detailed sections. At a minimum you should include the following segments:Contact informationResume summary statementWork experienceSkillsEducationHowever, to stand out to employers looking at your abilities as a machine learning engineer you should aim to include a few highlights that mark you out as a unique candidate. This can include one or more of the following optional sections:ProjectsCertifications and coursesHobbies and interests . It’s better to keep your resume short and sweet. Ideally, you should stick to a length of about 1-2 letter pages. Don’t go beyond 2 pages, however, as longer resumes are often not read in their entirety or are simply discarded by particularly busy recruiters. Resumes of 3+ pages are not competitive and will not give you an advantage even if your profile is tip-top. Machine Learning Engineer Resume Section Headings . Work experience . Your work experience section is what recruiters will be scrutinizing first and foremostly. This means striking a fine balance between the details they will want to see on the page with keeping things concise.You should only include the most recent (within the last 10 years) and relevant jobs that you’ve held. For each entry include the following aspects:The name of the company and its locationYour job title(s)The dates you were employed betweenThe tasks you took on and the responsibilities you were givenWhen you elaborate on the tasks you did, being specific is key. Demonstrate precise expertise in the particular fields of data science and management you’ve undertaken. For example, whether it’s in the financial, security or IT sector. You should also highlight any and all tools and data management systems you used to do the job.One of the most important elements to highlight in the work experience section, however, are the KPIs you worked towards and how well you met them. Recruiters are eager to see examples of what you brought to the company and how you helped them achieve success, and this is one of the best ways of doing so. Skills . It’s safe to say that working as a machine learning engineer requires a broad range of abilities. Therefore a well-stocked resume skills section is essential to success. Depending on the role and the knowledge required by the employer in question, you should seek to include one or more of the following talents on the page:Hard skills:StatisticsCodingQuality controlSoftware engineering and designData structuresProgramming languagesData miningSoft skills:Attention to detailProblem-solvingSimplifying complex informationCommunicationCritical thinkingAnalytical mindset Education . You’ll need at least a Masters’s or Bachelors’s degree to get hired as a machine learning engineer. An MS or BS in Computer Science, Computer Engineering or Computing will normally fulfill the requirements sought out by hiring managers.Further to this, it’s also wise to include any and all information about any courses or training you’ve had in a relevant system or coding language. These can also be expressed in the education section of the resume or can be included in its own section dedicated to certifications. Last modified on November 30th, 2021 Related Samples . .NET Developer resume Blockchain Developer resume Cyber security analyst resume Java Developer resume Full stack developer resume Computer Scientist resume Computer Repair Technician resume C Programmer resume Incident Manager resume Director of Information Technology resume Support. Terms & ConditionsTerms of UsePrivacy PolicyCookies PolicyFAQ  Copyright 2022    All rights reserved Jobless due to COVID? Let Resume Coach help you get your next job ASAP.
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Result 22
TitleMachine Learning Engineer Resume Example With Content Sample | CraftmyCV
Urlhttps://craftmycv.com/resume-examples/machine-learning-engineer
Description
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Organic Position22
H1Machine Learning Engineer Resume Example With Content Sample
H2How to Effectively Write a Machine Learning Engineer Resume?
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H2WithAnchorsHow to Effectively Write a Machine Learning Engineer Resume?
BodyMachine Learning Engineer Resume Example With Content Sample Machine Learning developers are experts or skilled in utilizing data to training models. These models are then used to automate procedures or processes like speech recognition, market forecasting, and image classification. Your responsibilities as a machine learning Engineer include knowing business goals and developing models, which assist in obtaining them, together with metrics to monitor or track their developments. You have to manage available resources like data, hardware, and personnel to meet deadlines. It would help if you also analyzed the machine learning algorithms, which can solve any issue and rank them by their success likelihood.To qualify for the position, you must have proven experience as a ML Engineer or the same role. You must have in-depth knowledge of math, algorithms, and statistics. You must have the skills to work in a team and a graduate of BS in Computer Science, Mathematics, or the same field. Create your Machine Learning Engineer Resume by clicking on ''Use this Resume'' button. Machine Learning Engineer Resume Example With Content Sample Use this Resume How to Effectively Write a Machine Learning Engineer Resume? . To enhance the chance of getting the job you want, you must first come up with a well-written resume. Here are the tips on how to do so:Write a Great SummaryMake sure you have a well-written summary for your resume. This can help you convince the employer to read your resume. The summary must be packed with essential information like your characteristics, achievements, skills, etc., but ensure that it is short and brief.Include Relevant SkillsAnother thing to consider is to include the skills relevant to the position you are applying for. Be honest and ensure that you possess these skills. You can write 4 to 6 skills. With that, the recruiting manager can have an idea about your competency to be a responsible employee. Mention Achievements To increase the chance of getting the job you want, ensure to mention relevant achievements. But, see to it that these accomplishments are relevant to the position of machine learning developer. You can write your professional experience to give them useful information regarding your achievements. This gives you the chance to be a machine learner Engineer on the firm you are applying for. One important tip is that make sure to write the resume using easy to understand and professional wording. Avoid vulgar words at all times. Summary. Passionate about cutting edge technology and solving real-world problems. With previous experience in managing financial risks, I want to lead a lean team and develop new products. Professional Experience . Azure Jul, 2014 – Present Machine Learning Engineer Azure is one of the leading organizations in AI algorithm development focused on creating better traffic systems. Work with Data Scientists and Product Managers to frame a problem, both mathematically and within the business. Deployed validated algorithms to  RTB system and developed techniques for monitoring and visualizing the performance of all deployed algorithms. Azure May, 2011 – Jun, 2014 Machine Learning Researcher Azure is one of the leading organizations in AI algorithm development focused on creating better traffic systems. Worked closely with development teams to ensure accurate integration of machine learning models into firm platforms. Developed high impact capabilities in data science and machine learning, and applied them to create new data-driven insights. Created innovative and systematic investment signals and strategies based on a rigorous, peer-reviewed research process. Quote . favourite quote. There is no easy way from the earth to the stars. ~Seneca Achievements. 2014 Lane Finding & Vehicle Detection Built an advanced lane finding algorithm with Python and Open CV using distortion correction, image rectifications, color transforms, and gradient thresholding.  2016 The Nature Conservancy Fisheries Monitoring Designed an ensemble of three different models, that leverages from transfer learning using award-winning architectures for computer vision, to successfully identify fishes in an image captured from fishing boats. Key Skills. Applying Machine Learning Computer programming Managerial Statistics Data-Modeling Data evaluation System Designing Languages. English (Native) Dutch (Basic) Polish (Basic) Education. Bachelor’s Degree in Computer Science Johnson University May 2006 - Jun 2007 Mater Degree in Computer Science Johnson University Aug 2005 - May 2006 Certifications. iTECH Art Groups Prof. Certificate in Data Science Aug 2008 Sigma Data Systems e Cornell Machine Learning Certificate Apr 2016 Interests. Backpacking Trekking Camping Cricket Playing Piano Astronomy Social Media. Facebook /John.Doe Linkedin /John.Doe Instagram /John.Doe In 3 years. In the next 3 years I want to develop an algorithm to identify vacant parking lots in a city and reduce the parked vehicle traffic on the roads. Click on “Use this Resume” to automatically fill the content in your Machine Learning Engineer Resume. Get Noticed. Get Hired. Craft your own Machine Learning Engineer Resume. HR Approved Resume Templates World's First Mobile Resume ATS Ready Resume in Word Format SEO-friendly Online Resume 25000+ Resume Content Suggestions Pre-written Resume For Quick Editing Get Noticed. Get Hired. Create Machine Learning Engineer Resume in minutes Use this Resume Sign Up. Sign up with Linkedin Facebook Google Already have an account? Sign in here Thank you for Signing up! You?re nearly there! We?ve emailed the verification link to [email protected] Not your Email? Please check your inbox now! Click the link in the email to verify your email address. Didn?t recieve email yet? Please check your mail and please check your spam box as well. Resend confirmation email Sign In. × or Linkedin Facebook Google No account yet? Signup for free We care about your data, and we'd love to use cookies to make your experience better. Privacy Policy Okay! loading...
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Result 23
Title15+ Machine Learning Projects for Resume with Source Code
Urlhttps://www.projectpro.io/article/machine-learning-projects-for-resume/466
DescriptionMachine learning projects for resume that you can add to show how your machine learning skills and experiences fit into the ML job role you're applying for
DateDec 30, 2021
Organic Position23
H115+ Machine Learning Projects for Resume with Source Code
H2Table of Contents
Machine Learning Projects for Resume - A Must-Have to Get Hired in 2021
Machine Learning Projects for Resume - The Different Types to Have on Your CV
New Projects
Machine Learning Project Ideas for Resume
Explore Categories
Get confident to build end-to-end projects.
Most Watched Projects
How to List Machine Learning Projects on Resume?
FAQs on Machine Learning Projects for Resume
H31. Machine Learning Projects on Classification
2. Machine Learning Projects on Prediction
3. Machine Learning Projects on Computer Vision
4. Machine Learning Projects on Natural Language Processing (NLP)
5. Deep Learning and Neural Network Projects
6. Machine Learning Projects on Time Series Forecasting
1) Machine Learning Projects for Resume on Classification
Sentiment Analysis ML Project for Product Reviews
Building Recommender Systems
Spam Email Filtering
2) Machine Learning Projects for Resume on Prediction
Machine Learning Project Ideas on Prediction Problems
Sales Forecasting
Weather Forecasting
Customer Churn Prediction
3) Machine Learning Projects for Resume on Computer Vision
Machine Learning Project Ideas on Computer Vision
Face Recognition
Building an OCR System from Scratch
Image Restoration - Denoising Images
4) Machine Learning Projects for Resume on NLP
Machine Learning Project Ideas on NLP
Build a Chatbot
Speech Recognition
Topic Modelling
5) Deep Learning and Neural Networks Projects for Resume
Deep Learning and Neural Network Project Ideas for Resume
Self-Driving Autonomous Cars
Natural Language Translation using Deep Learning
Credit Card Anomaly Detection using Autoencoders
6) Machine Learning Projects for Resume on Time Series Data
Machine Learning Project Ideas for Resume on Time Series Data
Weather Forecasting
Sales Prediction
Stock Prediction
H2WithAnchorsTable of Contents
Machine Learning Projects for Resume - A Must-Have to Get Hired in 2021
Machine Learning Projects for Resume - The Different Types to Have on Your CV
New Projects
Machine Learning Project Ideas for Resume
Explore Categories
Get confident to build end-to-end projects.
Most Watched Projects
How to List Machine Learning Projects on Resume?
FAQs on Machine Learning Projects for Resume
Body15+ Machine Learning Projects for Resume with Source Code Machine learning projects for resume that you can add to show how your machine learning skills and experiences fit into the ML job role you're applying for. Last Updated: 30 Dec 2021 Get access to Machine Learning projects View all Machine Learning projects Sending out the exact old traditional style data science or machine learning resume might not be doing any favours in your machine learning job search. With cut-throat competition in the industry for high-paying machine learning jobs, a boring cookie-cutter resume might not just be enough. What if we told you there is a simple addition to your machine learning engineer resume to increase your chances of landing a lucrative ML engineer job.  You would add it in a jiffy, right? Well, yes, there is. All you need to do is highlight different types of machine learning projects on your resume.  The best way to showcase you have the required machine learning skills is to highlight how you’ve mastered those skills practically. Classification Projects on Machine Learning for Beginners - 1 . Downloadable solution code | Explanatory videos | Tech Support Explore Project Table of Contents. Machine Learning Projects for Resume - A Must-Have to Get Hired in 2021 Machine Learning Projects for Resume - The Different Types to Have on Your CV 1. Machine Learning Projects on Classification 2. Machine Learning Projects on Prediction  3. Machine Learning Projects on Computer Vision  4. Machine Learning Projects on Natural Language Processing (NLP) 5. Deep Learning and Neural Network Projects  6. Machine Learning Projects on Time Series Forecasting  Machine Learning Project Ideas for Resume 1) Machine Learning Projects for Resume on Classification Sentiment Analysis ML Project for Product Reviews  Building Recommender Systems Spam Email Filtering 2) Machine Learning Projects for Resume on Prediction  Machine Learning Project Ideas on Prediction Problems  Sales Forecasting Weather Forecasting Customer Churn Prediction 3) Machine Learning Projects for Resume on Computer Vision   Machine Learning Project Ideas on Computer Vision Face Recognition Building an OCR System from Scratch  Image Restoration - Denoising Images  4) Machine Learning Projects for Resume on NLP  Machine Learning Project Ideas on NLP Build a Chatbot Speech Recognition  Topic Modelling 5) Deep Learning and Neural Networks Projects for Resume Deep Learning and Neural Network Project Ideas for Resume Self-Driving Autonomous Cars Natural Language Translation using Deep Learning  Credit Card Anomaly Detection using Autoencoders  6) Machine Learning Projects for Resume on Time Series Data Machine Learning Project Ideas for Resume on Time Series Data Weather Forecasting  Sales Prediction  Stock Prediction  How to List Machine Learning Projects on Resume? FAQs on Machine Learning Projects for Resume Machine Learning Projects for Resume - A Must-Have to Get Hired in 2021. Machine Learning and Data Science have been on the rise in the latter part of the last decade. Thanks to innovation and research in machine learning algorithms, we can seek knowledge and learn from insights that hide in the data. Data Engineers, Data Scientists, Data Architects have become significant job titles in the market, and the opportunities keep soaring. Machine Learning Trends in Recent Years Deep Learning Trends in Recent Years With the global machine learning job market projected to be worth $31 billion by the end of 2024 and fierce competition in the industry, a machine learning project portfolio is a must-have. We’ve compiled a list of machine learning projects for a resume to help engineering students or anyone wanting to pursue a machine learning career stand out like GitHub Copilot in the interview. A strong machine learning resume includes different types of machine learning projects. What’s better, we have categorised them into different types, so you can include one project of each type to upgrade your resume with a versatile machine learning skillset for your next ML job interview. Every domain of machine learning presents its challenges and solutions. Hence, having diverse types of machine learning projects for your resume helps recruiters understand your problem-solving approach to various business problems. A typical machine learning project involves data collection, data cleaning, data transformation, feature extraction, model evaluation approaches to find the best model fitting and hyper tuning parameters for efficiency. Building an ML project from scratch ensures understanding of every step in the machine learning project lifecycle.  Machine Learning Projects for Resume - The Different Types to Have on Your CV. The ML project types listed below are not exhaustive. Still, they cover diverse types of machine learning projects that can add value to a resume and also one should get hands-on practice before appearing for any data science or machine learning job interview. 1. Machine Learning Projects on Classification. Classification refers to labelling groups of data into known categories or classes. Having ML projects on classification listed on your resume help hiring managers to understand your skills on how to tackle any classification problem end-to-end and select the suitable classification machine learning algorithm. Quite similar to classification is clustering but with the minor difference of working with unlabelled data. Clustering defines the process of grouping together identical objects into individual clusters. So, you can add both classification and clustering related machine learning projects to your resume.  2. Machine Learning Projects on Prediction . Predictive modelling often uses historical data to learn and predict the likelihood of an event in the future. Historical data provides insights and patterns for making valuable business predictions—for example, predicting customer churn for an organisation in the next 30 days. Having prediction machine learning projects will help hiring managers to understand how the predictions made by an ML model you built can help organisations take action on a product or a service. 3. Machine Learning Projects on Computer Vision . Working on hands-on ML projects that employ machine learning algorithms like OpenCV, VGG, ResNet to make sense of real-world objects and environments will show your abilities on how you handle diverse computer vision tasks using machine learning. Some examples of such problems include real-time fruit detection, face recognition, self-driving cars, etc.  4. Machine Learning Projects on Natural Language Processing (NLP). NLP helps computers understand, analyse, and process human language to derive meaningful insights from it. Recognising handwritten letters, speech recognition, text summarization, chatbots, etc, are some projects that you can build to showcase your NLP skills. NLP projects are a treasured addition to your arsenal of machine learning skills as they help highlight your skills in really digging into unstructured data for real-time data-driven decision making. 5. Deep Learning and Neural Network Projects . Deep learning is a subset of machine learning and one of the most hyped machine learning techniques today. Add deep learning and neural network projects to your resume if you want to showcase your advanced machine learning skills.  Adding deep learning projects to your resume is not a must-have if you’re applying for entry-level machine learning job roles, but they are good to have.  6. Machine Learning Projects on Time Series Forecasting . Time series analysis and forecasting is a crucial part of machine learning that engineering students often neglect. Adding machine learning projects from time-series data is an important machine learning skill to have on your resume. Usually, the time element in the data has valuable information for a machine learning model to glean insights, but at times, it could lead to insights that might not be real. Showcasing time-series projects on your resume will highlight your ability to identify the challenges associated with working with time series data and how you tackle those challenges before it’s too late. Top 30 Machine Learning Projects for Beginners  New Projects . ML Model Deployment on AWS for Customer Churn Prediction View Project Build an AWS ETL Data Pipeline in Python on YouTube Data View Project AWS MLOps Project to Deploy a Classification Model [Banking] View Project Tensorflow Transfer Learning Model for Image Classification View Project Build a Graph Based Recommendation System in Python View Project Build Deep Autoencoders Model for Anomaly Detection in Python View Project AWS MLOps Project for ARCH and GARCH Time Series Models View Project Build a Customer Churn Prediction Model using Decision Trees View Project Loan Eligibility Prediction Project using Machine learning on GCP View Project Recommender System Machine Learning Project for Beginners-3 View Project View all New Projects Machine Learning Project Ideas for Resume. Let's delve into the different types of ML project ideas in more detail. 1) Machine Learning Projects for Resume on Classification. Classification in machine learning is a technique that classifies data into selected classes or labels. Syntactically or semantically similar data form one particular class. The classes are referred to as collections, labels or targets as well. A typical classification problem is to identify the class for a given data point or instance.   The principle behind classification problems is to feed large amounts of data to the model and check for prediction accuracy using supervised learning. The idea is to try multiple models and assess the best-suited algorithm for the problem. Since real-world problems are peculiar and characteristic, it is imperative to check for different models before deciding which machine learning model best fits a given use case.  Machine Learning Project Ideas for Classification Problems Sentiment Analysis ML Project for Product Reviews . Sentiment Analysis is the process of identifying the emotions/sentiment in a text. Companies commonly use it to infer social media reviews, customer response and brand reputation. Sentiment analysis segregates the core of the sentiments into four main categories.  Polarity is the tonality of the text—Ex, negative, positive or neutral. Emotion signifies happiness, sadness, anger or confusion.  Urgency means the graveness and criticality of the text, namely urgent or not urgent. Intention infers whether a customer is interested or not interested. Pairwise Ranking and Sentiment Analysis of Customer Reviews The data set for the project contains over 1600 product reviews for medical products, which have been labelled as informative and non-informative. The project’s goal is to perform sentiment analysis on the reviews and rank them in their order of relevance. We start with preprocessing and cleaning the data which is sent to the feature extraction module. After the features are collected and vectorised, we proceed with the classification. Random Forest algorithm is used and performs reasonably well with an accuracy of 85 per cent and above. Finally, pair-wise ranking is done for each review against every other review. E-Commerce Review Sentiment Analysis Project with Guided Videos Building Recommender Systems. Recommender systems suggest similar items, places, movies, objects based on a person’s personality, preferences, and likings. Behind the scenes, it groups people with similar tastes together and recommends items from their collective repertoire. Recommender systems are widespread in the industry, with massive applications in eCommerce(Amazon), media(Netflix), and financial institutions (PwC). Content-based filtering and collaborative filtering are the most common techniques employed in the implementation of recommender systems. Music Recommendation System on KKbox Dataset The project aims at predicting if a user will listen to a song again in a period. KKbox provides a dataset for the project in user-song pairs and the first recorded listening time, along with song and user details. Outliers in the dataset are dropped, and null values are imputed.  The XgBoost algorithm is used to predict the chance of relistening with the highest accuracy.  Music Recommendation System Project with Guided Videos  Spam Email Filtering. Spam mail classification labels suspected emails as spam and stop the mails from reaching the mailbox. It checks for the mail content, specific signatures and suspicious patterns to learn about spam mails. There are many techniques available to filter out spam emails - Content-Based Filtering Content-Based Filtering creates automatic filtering rules by analysing words, the occurrence of specific words and phrases in the mail.  Rule-Based Filtering Rule-Based Filtering uses already created rules to score the message in the text by comparing the regular expression. If a text matches a certain number of threshold rules, it is tagged and spam, thus dropped. The rules are updated periodically to keep up with the variety and novelty in spam messages. Case-Based Filtering Case-Based Filtering is among the more popular filtering techniques where spam and non-spam emails are added to a dataset. The dataset goes through the preprocessing stage, and all the emails are converted to two vector classes, spam and nonspam. Learning algorithms are applied to the vectors to classify them as spam and non-spam emails. And finally, testing for new mails occurs on the model.  Adaptive Spam Filtering Adaptive Spam Filtering classifies spam emails into various classes. The complete email dataset is divided into groups with emblematic signatures—the algorithm checks for similarities between the incoming mails and the groups and classifies the mails accordingly.  You can use the day to day email exchanges that are tagged as spam and not spam as the dataset for this ML project idea. The data goes through preprocessing steps like stop words removal and vectorisation, which return the data set in a vector form ready for modelling. The model trains using Logistic regression with an accuracy upwards of 90 per cent. An output class of 1 means that the mail is spam where zero signifies not-spam and one as spam.  Another popular classification algorithm called Naive Bayes Classifier also provides good accuracy.  Get Closer To Your Dream of Becoming a Data Scientist with 70+ Solved End-to-End ML Projects 2) Machine Learning Projects for Resume on Prediction . A prediction problem in machine learning is the most common, at par in occurrence with classification problems. Predictions take historical data and find the insights and trends hidden in the dataset.  The larger the dataset we have for training, the better and more accurate the prediction algorithm becomes. The current and historical data is taken to build a model that can predict events or trends in the future. The predictions can range from the potential risk of a credit card issue request to calculating the stock prices for a multinational company. Machine Learning Project Ideas on Prediction Problems . Sales Forecasting. Forecasting future sales depends on many factors like past sales, seasonal offers, holidays and festivals etc. Future sales also dictate staff requirements and stocking product inventory for future needs. Autoencoders and multivariate models can make a good fit for forecasting prediction problems where time is an added constraint.  Rossmann Store Sales Prediction Project The dataset contains historical data from more than 1000 Rossmann drug stores, including customer id, sales, store, state holidays, etc. Missing data points are imputed, and outliers get removed. Data is converted into numerical form by using one-hot encoding for easier manipulation. Stochastic Gradient Descent and Decision Tree regressor algorithms are mainly used in the model.  Project to Forecast Future Sales of Rossman Store with Guided Video Weather Forecasting. We tend to look at the weather report multiple times in our daily life. Predicting rainfall is of utmost importance to industries that depend on rains like agriculture. Weather predictions are relatively challenging and better done using Deep Learning algorithms. Even so, traditional ensemble models can offer outstanding results with the need for high resources.  The project’s data set is featured at Kaggle with information on the date, the average temperature on land and sea, minimum and maximum temperature on land and sea. The previous value replaces null values in the dataset, and date entries are converted to a DateTime object. The Zero-differentiated ARIMA model is used for prediction as, along with being a prediction problem, weather forecasting is also a time series problem. Finally, the accuracy is measured by Akaike Information Criterion.  Customer Churn Prediction. Customer churn is the behaviour of customers to stop using an organisation’s products or services. Customer churn rate is the rate of people who discontinue paid services in a particular interval of time. Churn is bad for companies as they lose revenue. Churn prediction finds applications in telecom, music and movie streaming services or other subscription-based services. Churn also signifies the health and reputation in the market for a company. Customer Churn Prediction Analysis for Bank Records The dataset from the bank records stores customer name, credit score, geography, balance, tenure, gender, etc. Preprocessing, imputing and label encoding are the next steps that occur. The dataset goes through feature extraction at this stage, eliminating less essential fields, making the dataset manageable and more consistent. The Light Gradient Boost Machine or LGBM algorithm provides maximum accuracy and is preferred for this project. Being lightweight, it is suitable in the big production setting of a bank. Customer Churn Prediction Project with Guided Videos  3) Machine Learning Projects for Resume on Computer Vision  . Computer Vision combines machine learning with image/vision analysis to enable systems to infer insights from videos and images. For a computer, it becomes quite a challenge to interpret pictures and distinguish the features. While as humans, we have evolved over a long time with our vision as a central characteristic. For humans, using vision to recognise objects around us is almost second nature. Computer Vision offers the possibility for computers to develop the vision to assimilate and comprehend the world around them.  The main principle involved in computer vision is to break the image into pixels. Pixels are the most fundamental constituents of an image. By recognising the pattern in the pixel pool, computers begin the task of image identification. Equally important is what features we extract from these pixels and how we construct the learning model. Computer Vision Techniques Object Detection is the identification of objects in an image. These objects can be any person, thing, animal, or place but need distinctive features that the model uses to recognise and detect the subjects in the photos. Object detection happens through localisation, where a bounding box outlines the object. The object comprises many pixels, and those pixels belong to the same object class. Object detection is used in google photos, where google detects faces from our library of images. Object Tracking refers to following the path of a particular object in a situation or environment. Stacked Auto Encoders (SAE) and Convolutional Neural Network  Surveillance is an ideal example of object tracking.  Image Classification is tagging images under a class holding similar photos. An example of image classification is the annoying ‘Not a Robot’ authentication that forces one to select all the traffic lights in the image.  Image Segmentation Image segmentation aims to break the image into partitions or segments so that it’s easier to analyse and process the whole picture. There are two types of image segmentation possible, listed as follows: Instance Segmentation - It recognises each object of the same type as a new object. So an image of three elephants would be categorised into three separate elephant classes, namely, elephant1, elephant2 and elephant3. Semantic Segmentation - It understands the semantics in the pixels and labels semantically similar objects in the same class. Considering the elephant example from above, pixels in the image of three elephants will get tagged under only one elephant class, namely elephant. Get FREE Access to Machine Learning Example Codes for Data Cleaning, Data Munging, and Data Visualization Machine Learning Project Ideas on Computer Vision. Face Recognition.   Face recognition is a non-trivial computer vision problem that recognises faces and clusters them under appropriate classes. Face recognition finds uses in mobile phone applications, surveillance, photo tagging applications, google lens, etc. OpenCV is the most popular library that helps with building models for face recognition.  Face Recognition System in Python using FaceNet The dataset for the project is a video from the famous sitcom show called Friends. Frames per second from the video are extracted to form the dataset in which we need to recognise the cast’s faces. A total of 35 images, with seven images for each character, are collected. Haar Cascade Object is used for face detection and extraction, while Convolution Neural Network is used for model training.  Face Recognition Project using Facenet with Guided Videos Building an OCR System from Scratch . Optical character recognition is the technique of identifying the letters and digits in a handwritten document or bill. It extracts the relevant information from the documents and records it in the database. Since handwritings come in numerous styles, OCR needs extensive training and fine-tuning of parameters.  Building OCR in Python using YOLO and Tesseract The dataset for the project is created using the Labellmg tool in python to label all the invoices present. After the labelling, we proceed with the YOLOv4 ( you only look once ) algorithm to detect the invoice number, date and total bill amount. Next, Tesseract is used to read/predict text from the detected fields.  We also use image augmentation to expand the dataset to a considerable size if the dataset is small.  OCR Project Built from Scratch with Guided Videos  Image Restoration - Denoising Images . Image restoration is the reconstruction of old images to make them new-like with optimum quality and features. It takes into consideration both spatial information and frequency to replace missing values in a snap.  Explore Categories. Data Science Projects in Python Deep Learning Projects Neural Network Projects Tensorflow Projects H2O R Projects IoT Projects Keras Deep Learning Projects NLP Projects 4) Machine Learning Projects for Resume on NLP . Natural Language Processing is part of machine learning that involves understanding and processing human language, text, and spoken.  Here is a list of prevalent NLP tasks that will help in getting a sense of its wide array of applications: Speech Recognition Part of Speech Tagging Word Sense Disambiguation Named Entity Recognition Coreference Resolution Sentiment Analysis Natural Language Generation  NLP Techniques. Natural Language processing uses two effective techniques which differ in their approach to analysing language; they are namely: The Syntactical Analysis makes use of grammar to identify and analyse the natural language. It checks for sentence structure, the relationship between words and rules of grammar.  Remove Punctuation Punctuations clutter the data with useless tokens and don't add to the model efficiency. It's best practice to remove them beforehand.  Tokenisation is the breaking of sentences into smaller parts that can be either words or combination words. It makes data processing easier and uniform across the whole dataset. Lemmatisation is converting words to their most basic form called Lemma. The lemma replaces every other form of the word. For example, learning, learned, learnt, learnable shall be replaced with learning. Stemming is the process of dropping the beginnings and ends of words depending on their prefix and suffix.  Part of Speech Tagging labels tokens as a verb, adverb, adjective, noun etc., based on the grammatical vocabulary. It helps discern the difference between the noun and adjective forms of the same word if a comment has different meanings. For example, the word sense signifies the five senses and the act of perceiving.  Stop Words Removal focuses on deleting all the common stop words like a, an, the, and, like, just that don't add to the concrete meaning of the text. Vectorisation or Bag of Words is the process of counting the occurrences of individual words in a text. The count of each word helps in understanding how important the word is to the whole subtext. The Semantical Analysis uses the meaning of words instead of syntax to process sentences. It starts with the meaning of each word, then moves on to the meaning of a group of words and finally the meaning of the whole subtext.  Word Sense Disambiguation identifies different forms/meanings of the exact words depending upon the context of its use and neighbouring terms. Word Relationship Extraction tried to infer the relationships between different words in a sentence like a place, subject, object etc. Machine Learning Project Ideas on NLP. Build a Chatbot. Chatbots are NLP applications that enable us to query details and raise grievances in natural language to receive relevant information. Chatbots are prevalent in the customer service industry, where setting up call centres is cumbersome and not budget-friendly.  An example is the amazon chatbot that helps customers with order information, order cancellation etc.  Natural Language Processing Chatbot using NLTK The dataset is conversations from a leave enquiry and application system for the organisation. The textual data is pre-processed using various NLP techniques like lemmatisation, tokenisation, stemming and stop words removal. The occurrence of each word is counted to create a count vector model called a bag of words. You can use algorithms like Naive Bayes Classifier and Decision Tree for modelling.  NLP Chatbot Project with Guided Videos Speech Recognition . Speech recognition is the ability of a machine to understand human language and respond coherently with appropriate data. Speech recognition finds use in our daily life while we use maps, call a friend or translate language all through our voice. Alexa in Amazon Echo and Siri in Apple iPhones are some of the best examples of speech recognition.  Topic Modelling. Topic modelling is the inference of main keywords or topics from a large set of data. It measures the frequency of a word in the text and its relationship with neighbouring words to extract succinct information. Typical uses are labelling unstructured data into formatted topics. It can also be used in text summarisation problems with minor tweaks to the model.  Topic Modelling using K-means Clustering on Customer Reviews  The customer reviews for the project are sourced from Twitter for a particular company. Data goes through many layers of preprocessing as the twitter reviews are unfiltered and raw. Tokenisation and vectorisation are performed using TD-IDF and count vectoriser. Model training is done using k-means clustering, an unsupervised learning algorithm. The final result is clusters of tweets with different classes that signify the dominant topic in the cluster.  Topic Modelling for Customer Reviews ML Project with Source Code  Get confident to build end-to-end projects. . Access to a curated library of 120+ end-to-end industry projects with solution code, videos and tech support. Request a demo 5) Deep Learning and Neural Networks Projects for Resume. Deep Learning aims at mimicking and simulating human thought patterns by using complex and layered structures called Neural Networks. In simple terms, Deep learning is multiple Artificial Neural Networks connected. Neural networks can accomplish clustering, classification and regression with greater efficiency than traditional machine learning algorithms.  Deep Learning eliminates the feature extraction process and skips over this step essential to all the traditional machine learning algorithms. These classic algorithms, called flat algorithms, cannot use data without preprocessing or feature extraction. Feature extraction is a detailed and involved process that needs expertise in the problem domain and patience in refining it over time. Deep Learning straight away discards this step and moves on with raw data. Deep Learning can learn and model the problem satisfactorily upon many iterations by tuning the weights using loss functions.  A brief look at the architecture of a deep learning model Nodes - A neural network is a collection of primary cells called Nodes. A Node stores arithmetic values like 0.4,2.21 etc Weights are the branches that connect two nodes. They represent a number that keeps changing over the training time. The process of starting from a set of random weights to arriving with specific values that fits the input data is called Learning. Loss Function defines the difference between the prediction vector obtained from the Neural network and the actual output vector—the lesser the loss function value, the better the model.  Back Propagation of Errors pushes the errors back towards the input layer. In the process, it keeps updating the weights in each hidden layer. The principle behind this is that the total error gradient in the output layer is the sum of individual error gradients at each point in the network.  Gradient Descent is when the weights are tuned using the derivative of the loss function to improve the network. The idea is to bring the weights to a value that spawns the most accurate prediction.  The nonlinear activation function is applied to the dot product of the previous hidden layer vector and weights connecting the two participating layers.  A feature vector is the input vector that goes into the Neural Network through the input layer. It contains a vectorised form of the input. Prediction vector is the vector form of the output that the neural network produces. Input and Output layers - Input and output layers are a neural network’s first and last layers.  Input Layer is a set of nodes that represent a data point in vector form. For example, for image recognition models, the input layer would be the vectorised version of the image pixels.  Output Layer denotes the result of the Neural Network. It is again a set of nodes quite like the input layer, but these individual nodes represent the output classes of the problem. For example, in the image recognition problem, the output layer would be nodes corresponding to objects in the image like cars, sheep, women etc. Hidden Layers are the layers sandwiched between the input and the output layer. All the computations ( like weights tuning ) happen among these layers. Explore More Data Science and Machine Learning Projects for Practice. Fast-Track Your Career Transition with ProjectPro Deep Learning and Neural Network Project Ideas for Resume. Self-Driving Autonomous Cars. Autonomous-driving cars can navigate through traffic and control acceleration and speed depending on their environment. Perception, Localisation, Planning, control are the four central ideas in self-driving cars.  Perception is figuring out the environment and obstacles.  Planning is the trajectory from point A to point B Localisation is identifying the current location in the world. Control relates to steering angle and acceleration.    Most Watched Projects . Linear Regression Model Project in Python for Beginners Part 1 View Project Orchestrate Redshift ETL using AWS Glue and Step Functions View Project Build an Azure Recommendation Engine on Movielens Dataset View Project Machine Learning Project to Forecast Rossmann Store Sales View Project Data Warehouse Design for E-commerce Environments View Project View all Most Watched Projects Natural Language Translation using Deep Learning . Language translation is extremely important in international trade, discourses, education and media where two parties interact without any common language. It translates text or speech from one language to another. For example- Google translate is a google cloud application that offers text translation into various languages. It uses Transalatron to develop the learning model. Neural Nets used are LSTMs and sequenced RNNs with an encoder-decoder model.  Credit Card Anomaly Detection using Autoencoders . The project aims at detecting fraudulent credit card transactions so the system can curb them and charge the customer of only the actual transactions. The dataset contains records of credit card transactions that are legal and fraudulent which have been passed through PCA (principal component analysis)analysis to change the data fields into numbers. We also have transaction amount, the time difference between consecutive transactions, and fraudulent transaction each unique credit card. Neural networks and autoencoders are used in conjunction with each other for modelling. And finally, the accuracy of the model is measured using Mean Squared Error (MSE) with the ggplot2 package.  Credit Card Anomaly Detection Project with Guided Videos 6) Machine Learning Projects for Resume on Time Series Data. Time Series data helps predict an object’s behaviour compared to its older state in time. Time series is a dataset of continuous and periodic observations of the time instances attached to the data itself. Time Series finds use in many prediction scenarios like weather prediction, prediction for the price of an item, sales prediction, etc. It is much like prediction but with an added time constraint or feature, making it an altogether different problem of time-series forecasting. Generally more complex than traditional prediction projects. Datatypes in Time Series. Time Series Data are observations recorded at different instances in time for a set period.  Cross-Sectional Data Data values of more than one variable are gathered at the same time. Thus, freezing or capturing the state of a system as a single entity in time. That is why the word cross-section comes into play, which implies a time-print of the model. Pooled Data is the mixture of time-series data and cross-sectional data.  Types of Time Series Modelling. Time series forecasting further divides into two subcategories based on the number of variables in the model, which are as follows: Univariate Time Series Forecasting is when only one other forecasting variable is present in the model apart from time. For example, in a sales prediction model, the number of sales is the only one that will vary with time. Multivariate Time Series Forecasting model is one where multiple variables are changing with time. Naturally so, the forecasting depends on these variables as well. For example, the temperature during the day depends on many variables like rainfall, wind, overcast etc. So essentially, a model to predict the temperature would be a candidate for multivariate time series forecasting.   Overview of Seasonality and Autocorrelation in Time Series Data. Autocorrelation defines the similarity between a time series and its lagged version, showing the relationship between past and present values. Autocorrelation is also called lagged correlation or serial correlation. It ranges between the value of -1 to 1.  Seasonality signifies periodic fluctuations in the graph of time series. Quite simply, it means that the data in the sequence repeats after a specific time called the period. Seasonality is generally calculated over one financial year. Time Series Analysis and Forecasting Techniques . ARIMA or Auto-Regressive Integrated Moving Average combines three models, i.e. ‘AR’, ‘MA’ and ‘I.’ AR shows the evolving variable of interest regressing over its initial values.   MA shows that the regression error is the linear combination of error term values at previous instances.  I shows that the data values are replaced by differences in their values from older values.  Moving Average is so-called because each data point averages the data values before and after in the time series and creates a new time series. Moving Average highlights trends and trends cycle. It is ideal for univariate time series. Exponential Smoothing creates the new time series by average the weight values from the current time series. A Datapoint in a time series has less weight if it's older in time compared to a recent data point.  The theory being that recent data has more chance of reoccurring again. Access Data Science and Machine Learning Project Code Examples Machine Learning Project Ideas for Resume on Time Series Data. Weather Forecasting . Weather forecasting is a complex time series problem that uses past weather data and related parameters like wind pressure, overcast, wind speed etc., into account while forecasting future weather.  The dataset contains the average temperature recorded in 2000 stations over Helsinki for some time. The SARIMA or Seasonal ARIMA model is used to model, and the Root Mean Squared value is used to check the accuracy. Sales Prediction . Sales prediction in a company is again a time series problem that considers the month of the year, holidays around and seasons in predicting future sales. The sales data show a cyclic trend in data that repeat every year. The dataset contains product information such as item id, item weight, type of the item, item MRP, etc. The dataset undergoes imputing of null values and one hot encoding. Outliers are identified with boxplot and deleted accordingly. Gradient boost tree and xgboost algorithms are applied for modelling, but the most efficient algorithm turns out to be a neural net with MLPRegressor.  Project on Bigmart Sales Prediction with Guided Video tutorials Stock Prediction . Stock Market prediction depends on the historical stock records, geopolitical environment and company performance in recent times. It is a complicated prediction problem that involves time series along with deep learning. The data is taken from the EU stock market with fields like the German DAX stock index, UK stock index, etc. We extract the trend and seasonality in the dataset and identify correlations and autocorrelations. Vector Autoregression (VAR) is used for modelling with good accuracy among other algorithms like ARIMA and LSTM. Time Series Project on Stock Market with Source Code and Explanatory Videos How to List Machine Learning Projects on Resume? If you are a recent college graduate or in the final year of graduation, you know how difficult it is to create a data science or machine learning resume without prior work experience. However, adding diverse machine learning projects mentioned above can definitely add credibility to your resume. It is essential to treat the various types of machine learning problems discussed above as a general guide since each project is unique and needs a precise approach. One can start by learning one project in each category and proceed from there. It is crucial to take note of learnings from each project and list them in the resume.  Here’s a recommended list of blogs on different types of project ideas for further exploration and reading - 8 Newest Projects to Jump-Start the Data Science Journey Image Processing Projects Deep Learning Projects Data Science Projects 15 Data Mining Projects Ideas with Source Code for Beginners 20 Machine Learning Projects That Will Get You Hired in 2021 15 Data Visualization Projects for Beginners with Source Code 20 Web Scraping Projects Ideas for 2021 20 Machine Learning Projects That Will Get You Hired in 2021 8 Healthcare Machine Learning Project Ideas for Practice in 2021 FAQs on Machine Learning Projects for Resume. 1) How do you put machine learning projects on your resume? Machine Learning projects should be brief and to the point on the resume. One can briefly discuss the dataset, model training, libraries used and accuracy by mentioning only the crucial points.  2) Are Machine Learning projects good for a resume? Indeed, machine learning projects are great additions to one’s resume. Machine learning is a burgeoning field and adding ML projects to the resume opens up job more opportunities. Candidates who wish to make a career in Machine Learning or Deep Learning need to build a versatile portfolio of ML projects for the resume. 3) Can one do Machine Learning projects in an Internship? Yes, one can do machine learning projects in internships. In fact, during internships, one learns to build and deploy machine learning projects in real-time. It is an ideal environment to expand one’s experience and knowledge. But it is equally essential to be able to land an internship in the first place. It is best to start learning and practising machine learning projects at our own pace and slowly build an internship resume. By enlisting some prior understanding in machine learning projects, one can increase their chances of landing a machine learning internship.  4) What projects can I do with Machine learning? With Machine Learning, one can do many projects depending on the project type and theme.  A good strategy would be to pick one project from each category, as discussed above, for the resume. Face Recognition Project, Sales Prediction projects, Recommendation System Projects, Building a chatbot using NLTk, Spam mail detection project etc., are good choices to get started with gaining hands-on exposure to diverse kinds of problems. 5) How does one write a Data Science project for a resume?  A data science project for a resume should have a brief introduction followed by a one-line explanation about the dataset and data-cleaning techniques involved.  Following that, one should write about the models used and the model that produced maximum accuracy.   It is crucial to remember not to be long-winded in describing the project and mention the significant points.  In the end, you can conclude by remarking about the learnings obtained during the project and key takeaways. PREVIOUS NEXT   Get Free demo of AWS project. × Get Demo Now CONTINUE Download the Interview Guide. × Go, Get That Dream Job! CONTINUE
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Result 24
Titleresume.pdf - Andrey Kurenkov
Urlhttps://www.andreykurenkov.com/files/resume.pdf
DescriptionResearch Assistant, Stanford Vision Lab, Stanford CA. January 2017 - Present. Contributed to development and evaluation of novel Deep Learning CV research, part ...
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Result 25
TitleMachine Learning Skills on Resume | Top Machine Learning Skills List
Urlhttps://enhancv.com/resume-skills/machine-learning/
DescriptionMachine Learning skills examples from real resumes. Machine Learning skill set in 2022. What jobs require Machine Learning skills on resume. Read through Machine Learning skills keywords and build a job-winning resume
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Organic Position25
H1Machine Learning Skills: Example Usage on Resumes, Skill Set & Top Keywords in 2022
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H3How to use Machine Learning skills on your resume:
Types of machine learning skills to add in your resume:
How to demonstrate Machine Learning skills on your resume
What jobs require Machine Learning skills:
Machine Learning skills courses and certificates:
Here are the top related skills to Machine Learning:
Machine Learning popularity over time:
Looking to build your own resume?
Try our professional resume builder
H2WithAnchors
BodyMachine Learning Skills: Example Usage on Resumes, Skill Set & Top Keywords in 2022Volen Vulkov4 minute readUpdated on 2021-07-26The demand for machine learning talent has exploded in recent years. And there’s a growing need for companies to hire the best candidates for the job.Your machine learning skills section is a great way to stand out and get hired.Here are the machine learning skills every recruiter will look for in your resume:How to use Machine Learning skills on your resume:. ExperienceData ScientistStoresbridge Ltd.Jan/2014 - Feb/2019Credit policy re design using Machine Learning, and implementation led to a saving ~1.4 mn(2) Machine learning framework - Performed data exploration, planning of framework and feature engineering.Reduced in-quarter Deal Slippage by 4% by enabling Machine Learning based risk factorsMentored a batch of 10 students of 1st and 2nd year of engineering for the mathematical aspects of Machine LearningPrototyped and launched machine learning product used by Fortune 500 companiesPrepared maintenance schedules for 3 heavy equipment by Machine Learning and increase machine availability up to 95%.Provided $10MM in business value through machine learning and data analysisTypes of machine learning skills to add in your resume:. Data modeling and evaluationSystem designProgramming languages: C, C++, Java, PythonSoftware engineeringData analysis and interpretationML libraries & algorithmsSignal processing techniquesPRO TIPStill struggling to determine your most marketable machine learning skills? Write down as many skills as you can think of. Then, cut all the basic, repetitive ones. And only keep high-demand, industry-specific abilities that will get you hired.How to demonstrate Machine Learning skills on your resume. Selected machine learning libraries for different tasksDesigned new models and algorithms for machine learning projectsImplemented machine learning experiments that lead to the development of new algorithmsWhat jobs require Machine Learning skills:. Data ScientistSoftware EngineerData AnalystInternSoftware DeveloperInternshipData Science InternResearch AssistantWeb DeveloperMachine Learning InternRead our article on how to add language skills on resume for additional tips and tricks.Machine Learning skills courses and certificates:. Data Science and Machine Learning Bootcamp with RLearn how to use the R programming language for data science and machine learning and data visualization!Introduction to Machine Learning for Data ScienceA primer on Machine Learning for Data Science. Revealed for everyday people, by the Backyard Data Scientist.A-Z Machine Learning using Azure Machine Learning (AzureML)Azure ML (Machine Learning): Azure Machine Learning Studio, Machine Learning on cloud, Machine Learning without codingThe Complete Machine Learning Course with PythonBuild a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!Here are the top related skills to Machine Learning:. PythonSqlJavaRTableauDeep LearningC++HtmlJavascriptHadoopPandasCMysqlGitSparkMachine Learning popularity over time:. Courtesy of Google TrendsYou are about to make a career change? Then go through our 10 Career Change Resume Tips (with examples) and see what you’re missing out.About this report:. Data reflects analysis made on over 1M resume profiles and examples over the last 2 years from Enhancv.com.While those skills are most commonly met on resumes, you should only use them as inspiration and customize your resume for the given job.Looking to build your own resume?Enhancv is a simple tool for building eye-catching resumes that stand out and get results.Variety of custom sectionsHassle-free templatesEasy editsMemorable designContent suggestionsTry free for 7 daysVolen VulkovVolen Vulkov is a resume expert and the co-founder of Enhancv. He applies his deep knowledge and experience to write about career change, development, and how to stand out in the job application process.Try our professional resume builder. BUILD MY RESUME NOW*No credit card requiredCheck out more winning resume skills examples for inspiration. Learn from people who have succeeded in their job huntGis SkillsWordpress SkillsVba SkillsAs400 SkillsData Modelling SkillsStatistics SkillsData Warehouse SkillsArtificial Intelligence SkillsMainframe SkillsData Collection SkillsStatistical Analysis SkillsHadoop SkillsGet more inspirationNo spam, just information that will help you build a resume that makes you feel relevant and well represented.You have successfully subscribed!Your resume is just a click away. Highlight your achievements, attitude, and personality, so you can tell your story with confidenceBUILD NOWCette page est disponible en français.Voir iciDenna sida finns på svenska.Kolla härGet startedCreate Resume  →PricingTerms of ServicePrivacy PolicyHTML SitemapGoodiesResume BuilderResourcesSkill ExamplesResume ExamplesResume TemplatesCover LettersCareer counselingPackagesServicesMeet our customersCareer resourcesAbout usCompanyCareersBlogReviewsHelp© 2021. All rights reserved.Made with love by people who care.
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Result 26
TitleStefano Meschiari — Resume
Urlhttp://www.stefanom.io/resume/
DescriptionStefano Meschiari's personal website
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H1Stefano Meschiari, Ph.D
H2Data Science Technical Lead, Duo Security
H3Experience
Technical Skills
Education
Publications, Academic Honors and Awards
H2WithAnchorsData Science Technical Lead, Duo Security
BodyStefano Meschiari, Ph.D. Data Science Technical Lead, Duo Security. [email protected] GitHub LinkedIn I am an experienced data scientist with a background in scientific research. I have worked on projects that involved researching new algorithms and approaches to attacking hard problems, analyzing complex, label-poor datasets, building novel production ETL and ML platforms, helping to bring intelligent capabilities to fruition for users, and creating functional data tooling. I am comfortable with bootstrapping new ideas, and figuring out how to chip away at uncertainty, clarify and better define the solution space, and measure success. I enjoy working with cross-functional teams to create, polish, and evolve from napkin ideas to production. In particular, I love collaborating with product and design teams to coherently integrate data science into their vision, and helping them test out new concepts and visualizations with data science-driven prototypes and customer discovery. Experience. Technical Lead. Feb 2019-present Senior Data Scientist. Aug 2017-Feb 2019 Duo Security (Cisco) I lead the research and technical development of the data science platform that powers the Duo Trust Monitor product feature. My work at Duo includes: Develop pipeline components and infrastructure that analyze data, build models, and surface possible threats and authentication anomalies at scale, using Spark, SparkML, and H2O. Research foundational supervised and unsupervised algorithms tailored to the security domain, with a particular attention to simplicity, explainability, and scalability. Translate internal domain expertise into expert rule layers and heuristics. Analyze our vast authentication dataset to mine new patterns of suspicious behavior. Collaborate with the product and design teams to understand how to shape algorithms and visualizations to address with our customer needs, simplify their operations, and remove friction. Work with customers via interviews, observations, and testing advanced development of new capabilities. Product Data Scientist. Feb. 2016-Jun. 2017 Civitas Learning Created and improved on prototype machine learning tools and pipelines to model student outcomes. Prototyped new product ideas and internal tooling that employ machine learning, novel summary statistics and visualizations. Maintained and improved the custom modeling platform. Reduced training and scoring running time (and cloud costs) by half. Independently developed components for end-to-end Data Science projects: Machine learning models and custom classification algorithms using R, Scala and Spark and JavaScript. Back-end (Node.JS/Express, created new APIs and services exposing new functionality to internal services) Front-end (React, HighCharts, and custom-built components and visualizations). W. J. McDonald Postdoctoral Fellow. 2012-2016 SAVE/Point, Principal Investigator. 2014-2016 University of Texas at Austin Led the data analysis effort for the Lick-Carnegie science collaboration (~20 scientists across the United States). Analyzed high-value time series data captured with Keck, APF and Lick telescopes using my Markov-Chain Monte Carlo code, Systemic. Systemic has been used to discover more than 40 new planetary systems. Wrote high-performance, parallelized codes to solve ordinary and partial differential equations modeling planet formation. Developed Super Planet Crash, an HTML5/JS game that was played more than 15 million times and was covered by The Verge, IO9, Huffington Post, and others; and Systemic Live, an HTML5/JS web app used at Caltech, UF, UT, MIT, SJSU, UD, Yale, Columbia, Coursera MOOC to teach students about data analysis and modeling. Technical Skills. Machine Learning: Building supervised & unsupervised classification and regression pipelines via state of the art and custom algorithms; devising high-performance statistical and numerical methods that run in production clusters; time series analysis and forecasting; architecting high-volume ETL and machine learning pipelines. Software engineering: Building projects from prototypes to production using R, Scala, Python, JavaScript, Java, and C. Experienced in using SQL. Experienced in building functional front-end prototypes. Soft skills: Cross-team collaboration, project management, and leadership; mentoring and advising. Education. 2012 – Doctor of Philosophy (Astronomy & Astrophysics), University of California at Santa Cruz. Received Whitford Prize for highest achievement in research, coursework, and teaching. 2006 – Master of Science (Astronomy, with highest honors), University of Bologna 2004 – Bachelor of Science (Astronomy, with highest honors), University of Bologna Publications, Academic Honors and Awards. Published 8 first-author publications on time series analysis, numerical optimization, and Monte-Carlo simulations (cited 224 times); a total of 17 refereed papers (cited 992 times). See research page. 2014 – Meschiari, S. (PI), Ludwig, R., Green, J., Interactive Education Tools in the Public Square (Award: $2,800, for creating an interactive outreach experience); Bringing the Tools of Research Direct to the UT Classroom: Systemic, a Virtual Lab for Students (Award: $87,710) 2010 – Award for Excellence in Teaching 2008 – Whitford Prize for graduate academic performance 2006 – Regents’ Fellow, University of California
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Result 27
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TitleData Scientist Resume Examples (PDF & Web)
Urlhttps://standardresume.co/examples/data-scientist
DescriptionTired of poorly written and obviously fake resume examples? Here are the actual Data Scientist resumes that got our customers hired at top tech companies. Junior and senior examples, as well as PDF and web templates
DateMay 10, 2021
Organic Position28
H1Data Scientist Resume Examples
H2Resume examples
Machine Learning Engineer
Work Experience
Square Inc
Square Inc
Framed Data
Flight Data Services
NCR Corporation
Education
Lancaster University (UK)
University of Portsmouth (UK)
Projects
Attention Fusion Networks: Combining Behavior and E-mail Content to Improve Customer Support
Deep Learning in Customer Churn Prediction: Unsupervised Feature Learning on Abstract, Company Independent Vectors
Skills
Software Developer & Data Scientist
Work Experience
Articulate Research
KINKBNB
Figure8Labs
Circus Automatic
MediaPilote Paris
Logikart
Education
University of California, Santa Cruz
General Assembly
Udacity
Skills
Resume Writing Tips
Resume Templates
H3Resume Format and Sections
Resume Template
Data Scientist Skills
Remote Jobs
Professional
Modern
Creative
Simple
H2WithAnchorsResume examples
Machine Learning Engineer
Work Experience
Square Inc
Square Inc
Framed Data
Flight Data Services
NCR Corporation
Education
Lancaster University (UK)
University of Portsmouth (UK)
Projects
Attention Fusion Networks: Combining Behavior and E-mail Content to Improve Customer Support
Deep Learning in Customer Churn Prediction: Unsupervised Feature Learning on Abstract, Company Independent Vectors
Skills
Software Developer & Data Scientist
Work Experience
Articulate Research
KINKBNB
Figure8Labs
Circus Automatic
MediaPilote Paris
Logikart
Education
University of California, Santa Cruz
General Assembly
Udacity
Skills
Resume Writing Tips
Resume Templates
BodyData Scientist Resume ExamplesUpdated by Riley Tomasek on May 10, 2021Tired of poorly written or obviously fake resume examples? Here are the Data Scientist resumes that impressed recruiters and got our customers hired. Use them as inspiration while writing your resume and picking a resume template.Machine Learning Engineer. View full resumeUse this templatePhilip SpanoudesMachine Learning EngineerSan Francisco, CaliforniaData Scientist / Machine Learning Engineer with a specialization in the design and implementation of deep/machine learning algorithms. Industry experience in: predictive modelling, optimization problems and simulations.PSWork Experience. Square Inc. Senior Machine Learning Engineer | Apr 2019 - CurrentTech lead on the Square Measurement Science team. The team is responsible for all forecasted internal metrics that are utilized from multiple teams across Square for quarterly/annual planning and investment portfolio optimization.Consulted on the design & development of various projects within the team. Helped by identifying possible gaps/roadblocks and suggesting ways on how to overcome these risks.Formed a small independent team of MLE's within Square and contributed to the design and implementation of a framework for deploying trained ML models as a service. The framework facilitated the application of ML models where real-time scoring was necessary.Enhanced existing merchant value forecast models to take into account the observed effects as well as speculated effects of the COVID-19 pandemic.Built a framework that facilitates the training of predictive models that are used to forecast a merchant's value across various Square products.Improved merchant churn prediction model, significantly decreasing the false positive rate in the upper score range. This in turn increased the amount of relevant case generation for the merchant retention program, meaning an ~ $11,000 improvement in daily ROI.Square Inc.Machine Learning Engineer | May 2016 - Apr 2019Part of the initial Square Capital Data Science team that was tasked with the continual optimization of all lending product design, marketing strategies and servicing techniques.Improved the internal rate of return (IRR) forecasting model for the Capital Flex product.Designed and implemented a product simulation framework that is used to evaluate the effects of model swaps and loan facilitation methodology alterations.Designed and implemented a heuristic optimization framework for product eligibility that searches for optimum threshold configurations based on expected loss and volume.Designed and implemented an email servicing model for automated solution suggestions to email inquiries.Improved the pre-existing loss forecasting model for the Capital Flex loan product.Designed and implemented an account servicing model that is used to identify high risk customers.Designed and implemented a Capital acceptance model for the marketing team that uses merchant event patterns to determine the probability of product acceptance.Created and was responsible for the team's model hosting framework and development environment.Framed Data. Data Scientist | Nov 2015 - Apr 2016Hired as Framed Data's principal research scientist with the sole task of improving the company's churn prediction algorithms for each customer.Researched and implemented a novel machine learning pipeline for arbitrary customer churn prediction.Invented a generalized data representation architecture that can be applied on different raw event company data.Implemented a state-of-the-art Deep Learning architecture that effectively decomposed complex user event patterns and ultimately increased prediction accuracies.Flight Data Services. Data Science Intern | May 2014 - Aug 2014Summer Data Science internship which helped in the uncovering of interesting patterns in flight sensory data to help with our flight operation quality assurance reporting to customers.Applied statistical analysis, machine learning and data mining techniques on vast amounts of flight sensory data.Identified patterns and interesting associations between combinations of flight data variables.Designed and generated visualizations that helped with the interpretation and explanation of the identified patterns within the FOQA product.NCR Corporation. Software Developer | Jun 2012 - Aug 2013One year placement at NCR (EMEA HQ) as part of the BSc. (Hons) Sofware Engineering course at the University of Portsmouth.Developed parts of the system that are currently being used by the Inland Revenue Department in Cyprus.Experienced different development life-cycles including Agile methodologies.Performed extensive Testing and produced Product Manuals for audiences of various technical knowledge.Education. Lancaster University (UK). Master of Science in Data Science Distinction | Sep 2014 - Nov 2015Best Overall Student Performance Award: Prestigious award in recognition for best student performance across all degree modules.University of Portsmouth (UK). Bachelor of Science in Software Engineering First Class Honours | Sep 2010 - May 2014Projects. Attention Fusion Networks: Combining Behavior and E-mail Content to Improve Customer Support. Researcher | Jun 2018 - Nov 2018Research conducted at Square Capital for the purpose of automatically suggesting solutions to customer email inquiries. The research yielded a novel deep learning architecture that combines two disparate data sources when estimating its predictions.Deep Learning in Customer Churn Prediction: Unsupervised Feature Learning on Abstract, Company Independent Vectors. Researcher | Jun 2015 - Aug 2015Initial research performed for Framed Data as part of the MSc Data Science Degree dissertation at Lancaster University. The research work conducted proved that Deep Learning can be successfully applied in the field of customer churn prediction by yielding better prediction results while also bypassing the tedious feature engineering phase in a traditional machine learning pipeline.Skills. Machine LearningDeep LearningFeature EngineeringPythonJavaC++Apache SparkC#Software Developer & Data Scientist. View full resumeUse this templateAlexis Mattos-VabreSoftware Developer & Data Scientist San Francisco, CA | figure8labs.comI've always been a builder and analyst of systems, abstract or concrete. I currently am advancing my education in the direction of machine learning and artificial intelligence. With a solid basis in web programming and software architecture, I'm also a highly motivated, curious, innovative and results-oriented individual seeking a full-time position in a company where hybrid career types are valued.AMWork Experience. Articulate Research. Data Science & Data Visualization Consultant | Feb 2016 - CurrentUsed Caffe, Theano (Keras), Lasagne, scikit-learn, TensorFlow and custom algorithms to complete projects.Used libraries/tools such as D3 and Processing to create data visualizationsResearch in current social problems using public data (Basic Income & Poverty in the San Francisco Bay Area, Time-Banking) Policy development through data analysis and predictive analyticsKINKBNB. Data Product Architect & Software Engineer | Jan 2016 - CurrentCreated new rental reservation system in Django/Python with a fully integrated CMS, analytics and data visualization.Implemented the use of Docker and MicroServices.Managed and created sprints in SCRUM methodology.Created migration plan for legacy PHP system to new Django stack.Figure8Labs. Creative Technology Consulting | Jun 2008 - CurrentWeb, marketing, and communications consulting as well as development, design, and UX design.Clients include: Chanel, LVMH, Au Feminin, Le Manoir de Paris, Barbara Bui, FITC, Circus Automatic, SensoreeCircus Automatic. Technical Director | Jun 2014 - Aug 2016Networked wall of 45 LCD screens using Raspberry PIs and software in pythonManaged and developed code base for robotics developmentMediaPilote Paris. Technical Director | Mar 2010 - Mar 2011Advise and develop technical strategies for web and HCI projectsDevelop custom modules for the branded CMS using php, ajax, and css. Integrate creative and technical concepts, and advise on technical feasibility and cost.Logikart. Full-stack web developer | Dec 2007 - Jun 2008Created Modules in PHP and AJAX primarily to extend OScommerce. Maintained the webstore and servers for LOLLIPOPS, a webshop with an international presence (with over 100 physical boutiques worldwide)Education. University of California, Santa Cruz. BFA Fine Arts | Sep 2000 - May 2005General Assembly. Certificate Data Science | Feb 2016 - May 2016Udacity. Nanodegree Machine Learning | Jul 2016 - CurrentI'm currently pursuing a certificate program in Machine Learning and participating in the Beta version of the Self-driving car programming nanodegreeSkills. predictive analyticsstatistical analysispythonalgorithm developmentphpdata visualisationsplunkux designscikit-learnkerascaffedata visualizationdata analyticsResume Writing Tips. The following tips are based on what we've learned from helping over 100,000 job seekers create a resume with our resume builder.Resume Format and Sections. Impressing recruiters and hiring managers will be much easier if you include the info they are looking for, in the correct order. Here are the sections and order we recommend.Contact information: This should be at the top of your resume and easy to find. Make sure to include your email and phone number.Work experience section: This is the most important part of your resume. Focus on your work experience that is most relevant to the job description you're applying for and use short bullet points.Education section: Make sure to list any degrees or certificates that the job posting requests. Only include your GPA and courses if you're applying for entry-level jobs.Other sections: You can also include skills, languages, patents, side projects, etc if they are relevant to the job you're applying for. It's generally best to avoid references. Recruiters will ask for them later and they take up valuable space.Related articleData Scientist Resume: How To Show Off Your Analytical SkillsYou can write an effective data scientist resume with these valuable writing tips, resume sections to include, and formatting guidelines.Resume Template. While the contents of your resume are undoubtedly the most important part, a good resume template can increase your odds of getting an interview. Most requiters only spend a few seconds on their initial resume scan, you need to make them count.We've taken the guess work out of picking a resume template. Our templates are designed in collaboration with recruiters and hiring managers, and are styled from professional to modern.If the job application requires a cover letter, it should have similar formatting to your resume.Data Scientist Skills. Skills are an important part of a data science resume. You should analyze the job description you're applying for and make sure to include the requested skills in your work experience and skills sections. Focus on technical skills and omit soft skills like "problem solving". Recruiters ignore them.Here are some skills that are frequently included in data science job descriptions on our remote job board.Programming LanguagesPythonScalaPerlRSQLNoSQLCompetenciesMachine learningNLPBig dataRegressionHadoopTableauAlgorithmsData setsGitHubData managementData processingData modelingRandom forestSASHiveLarge data setsMicrosoft AzureAmazon web services (AWS)Remote Jobs. Data EngineerAbine,Database EngineerBoxSenior Database Reliability EngineerSpreedlySenior Data EngineerQuartzyAll Data Scientist jobsResume Templates. Hiring manager approved Data Scientist resume templates.View all templatesProfessional. View professional templatesModern. View modern templatesCreative. View creative templatesSimple. View simple templates
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Result 29
TitleMachine Learning Specialist Resume Example | Kickresume
Urlhttps://www.kickresume.com/en/help-center/machine-learning-specialist-resume-sample/
DescriptionGet more job offers & find inspiration for your resume with this outstanding Machine Learning Specialist resume example
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Organic Position29
H1Machine Learning Specialist Resume Example
H2Machine Learning Specialist Resume Example (Full Text Version)
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H2WithAnchorsMachine Learning Specialist Resume Example (Full Text Version)
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BodyMachine Learning Specialist Resume Example Get more job offers & find inspiration for your resume with this outstanding Machine Learning Specialist resume example. Download this resume example free of charge or alter it with ease in our HR-approved resume creator. Create My Resume Reviewed by Tomáš Ondrejka Co-Founder and CMO Share this page: link copied copy failed This resume was written by our experienced resume writers specifically for this profession. Create your resume now or edit this resume example. Was this sample helpful? Rate it! Average: 4.0 (2 votes) Related resume guides and samples. How to create an effective database administrator resume? How to build a compelling game designer resume? How to write a compelling information security analyst resume? How to build a professional IT support officer resume? How to create a captivating network engineer resume? How to craft a balanced programmer resume? Machine Learning Specialist Resume Example (Full Text Version). Lauris Kronbergs. Email address: [email protected] Phone number: 555-555-5555 Resume Summary. Self-driven and passionate Machine Learning Specialist who excels at developing machine learning systems and creating new software applications. Possessing a strong attention to detail, exceptional analytical skills, and the ability to solve complex problems, Lauris is an effective team player determined to achieve extraordinary results. Work experience. 06/2016 - 06/2020, Machine Learning Specialist, BMB Technologies, Inc., New York City, NY, United Kingdom Collaborated with colleagues on the development and implementation of new machine learning systems.Collected and analyzed data, created machine learning algorithms, and maintained and managed large databases.Conducted professional statistical analysis and pro-actively participated in the development of multiple software applications.Recruited and supervised 7 IT Interns and completed detailed reports on the progress of the assigned projects.Awarded the Employee of the Year for constantly performing excellent work and meeting all targets and goals. Education. 09/2012 - 05/2016, Computer Science, Columbia University, New York City, NY, United States GPA: 3.98 (Top 1% of the Program)Clubs and Societies: AI Society, Golf Club, TEDx Club 09/2008 - 05/2012, High School, Riga Dome Choir School, Riga, Latvia Graduated with Distinction (Grade 1 - A/excellent equivalent in all 4 subjects)The 2010 Principal's Award winner for achieving extraordinary academic resultsExtracurricular Activities: Computer Club, Engineering Society, Math Society Skills. Languages Latvian English Chinese Software Skills Microsoft Azure AI Platform Knime Google Cloud AI Platform TensorFlow Pytorch Strengths. Accuracy Action oriented Analytical Communication High achiever Independence Learning Agility Responsibility Strategic thinking Volunteering. 09/2014 - 05/2016, Founder & President, Columbia University AI Society Certificates. 05/2016, Certified Machine Learning Specialist, SAS Edit this sample using our resume builder. Edit Sample What is your resume score? Our resume checker compares your resume against the best resumes from our database. Scan your resume for issues and find out your resume score. Score my resume now Similar Job Positions. Front-End Developer Information Security Analyst Back-End Developer Humanities Scientist Social Scientist Agricultural Scientist Formal Scientist IT Support Officer Chemist Natural Scientist Tester UX-UI Related Science Resume Samples . Information Analyst Resume Example Technology Researcher at the the World Bank Resume Sample Hired by Quantitative Research Analyst Resume Example View Science Resume Samples Related Software Engineering Cover Letter Samples . Back-end Developer Cover Letter Example Firewall Engineer Cover Letter Sample Video Editor Cover Letter Sample Hired by View Software Engineering Cover Letter Examples Let your resume do the work. Join 1,300,000 job seekers worldwide and get hired faster with your best resume yet. Create My Resume
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Result 30
Titleresume.pdf - Ari Kamlani
Urlhttp://arikamlani.com/docs/resume.pdf
DescriptionAccomplished AI & Machine Learning (ML) professional skilled in leading strategic ... Computer Vision (CV), and Reinforcement Learning (RL) systems.
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Title3 Tips For Machine Learning Resume| How To Break Into Machine Learning? | Job Search Strategy
Urlhttps://hicounselor.com/video/how-to-break-into-machine-learning-job-search-strategy-3-tips-for-machine-learning-resume
DescriptionMachine Learning certification and Machine Learning Resume, both play an important role to enter into a Machine Learning role. This needs to be adequately supported with a lot more knowledge and skill. These requirements are highlighted and discussed herein. With the help of tools and resources which are adequately highlighted you can equip yourself to break into Machine Learning job
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Organic Position31
H1How To Break Into Machine Learning? | Job Search Strategy | 3 Tips For Machine Learning Resume
H2How to Break into Machine Learning
Helpful Machine Learning Certifications and Education
Best Job Search Strategy to Adopt
Important Tip to Make Your Machine Learning Resume Stand Out
Important Skills of a Machine Learning Engineer
Blogs to Follow to keep Abreast of Data Science Development
Importance of Math in Machine Learning
Best Problem Formulation in Machine Learning
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H2WithAnchorsHow to Break into Machine Learning
Helpful Machine Learning Certifications and Education
Best Job Search Strategy to Adopt
Important Tip to Make Your Machine Learning Resume Stand Out
Important Skills of a Machine Learning Engineer
Blogs to Follow to keep Abreast of Data Science Development
Importance of Math in Machine Learning
Best Problem Formulation in Machine Learning
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Know All about Machine Lear..
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BodyHow To Break Into Machine Learning? | Job Search Strategy | 3 Tips For Machine Learning Resume Machine Learning certification and Machine Learning Resume, both play an important role to enter into a Machine Learning role. This needs to be adequately supported with a lot more knowledge and skill. These requirements are highlighted and discussed herein. With the help of tools and resources which are adequately highlighted you can equip yourself to break into Machine Learning job. Machine Learning Nikunj Bajaj Machine Learning Engineer How to Break into Machine Learning. Start Small and Learn on the Job: Any candidate wishing to start his or her career in Machine Learning can adopt the strategy of joining a Machine Learning team or company as an engineer. In this way, you can have a hands-on learning in the job. There are some companies which invest in your learning capabilities and teach you.  Machine Learning Certification: Some companies require you to have prior experience in Machine Learning. Generally, only a fundamental and working knowledge is sufficient. Machine Learning certification of some sort is always helpful to have. Familiarity with basic data structures, algorithms, etc will help you smoothly enter this field.  Invest in Yourself: Self-learning at home is also very useful. There are some short-term programs where they teach you applied Machine Learning. Things like how to apply Machine Learning in the real world and the use of the associated tools along with the basic concepts of Machine Learning are taught.  Employ Online Resources: This requires commitment and time which people may be unable to devote. In this case, there are materials available online. Andrew Banks on Coursera or books like Learning From Data are very useful. Build some basic models by yourself by taking up some real-world data sets and using some open source tools.   Helpful Machine Learning Certifications and Education . A proper degree or a Masters or PhD in machine Learning signifies your understanding of the subject. To land a machine-learning job the interviewer is rarely bothered about your certificates. Instead, they care about whether you know your subject and its core concepts.  Instead of chasing certificates, invest time in brushing up your fundamentals.    Best Job Search Strategy to Adopt . Develop Expertise – Have some level of expertise in the subject of Machine Learning.  Develop Contacts – Nurture some contacts who could connect you with appropriate and relevant job openings. Go on sites like LinkedIn and give a shout out to all your connections.    Important Tip to Make Your Machine Learning Resume Stand Out. Be thorough in what you know and do well anything that you undertake.  Some Examples If you are writing code, do it well with a genuine interest of building a great system.  If you are managing a project where your technical contribution is less, then make sure you are doing that job right. If you are taking any small learning courses make sure you do it to understand and learn and not for the sake of certification only.   Do not put information on your resume with the sole intention of making your resume stand out. When you cannot back up your information with the right knowledge and answers it looks superficial and does not deceive anybody.  Instead, be upfront about your actual skillsets and qualification and convince the company to give you chance in Machine Learning based on your overall general aptitude.  Be ready to back all the skills highlighted on your Machine Learning Resume.   Important Skills of a Machine Learning Engineer. Problem Formulation Skill: Machine Learning has different paradigms with which to solve problems. Supervised learning, unsupervised learning and reinforcement learning are some different techniques with which you can formulate a problem. Each of these paradigms work well with certain kind of problems. This skill comes with experience. Problem formulation is one of the key skills in solving a Machine Learning problem.   Understanding Algorithms: Understand different algorithms like logistic regression, deep neural networks, etc. Each algorithm is better suited for certain kind of problem. Even when you have chosen a particular algorithm understand the nitty-gritty of it to suit best your particular problem. Know your fundamentals and algorithms. Coding: Ability to write code well is a very key skill to have. Being able to write code and experiment and deliver things end to end is very important. This implementation skill is much sought after.    Blogs to Follow to keep Abreast of Data Science Development. Blogs of most big companies doing AI research – Google, LinkedIn, Facebook, etc Read associated papers which give an insight into some of the more cutting-edge work Read papers in the reference sections of the main paper. This gives deep and broad knowledge of recent advancements.   Importance of Math in Machine Learning. The field of math has become very important in Machine Learning. Linear algebra in Machine Learning is basically dependent on how you operate on matrices. Most algorithms are optimized based on matrix manipulation and linear algebra comes in very handy.  Optimization techniques, differential calculus is also useful because you need to use a bunch of differentiation in your algorithms.  Even if you do not a background of maths, you can still manage If you have very good intuitive understanding of the algorithms and are able to fill in the blocks mentally with some mathematical equations and the tools and technologies available.    Best Problem Formulation in Machine Learning. Practice till you perfect Read blogs Learn from similar case studies Start-ups doing deep technical work provide a good insight Study how big companies handle these problems and the approach adopted by them Get into the mainstream and plunge into the work and start doing and solving problems to learn Take random data sets and try to formulate the same as a Machine Learning problem.  All the above steps will give you clarity from which you can learn and improve.   Other Video in this Category. Machine Learning Job Search Strategy And Car... Brad Miro Machine Learning Engineer Machine Learning Engineer job profile has various career paths such as Senior Machine Lear... Machine Learning Know More About Life As An... Brad Miro Machine Learning Engineer Machine Learning Engineer job is an alluring job profile that has its own share of challen... Machine Learning What Is Machine Learning | ... Brad Miro Machine Learning Engineer The ability of computers to learn from data is what Machine Learning is about. Traditional... Machine Learning Here Is All That You Need T... Brad Miro Machine Learning Engineer In the era of Artificial Intelligence Machine Learning is a great job title to pursue. The... Machine Learning Know All about Machine Lear... Brad Miro Machine Learning Engineer The speaker gives a detailed review of machine learning, the possible interview questions ... × To continue browsing, sign in with HiCounselor account. Forgot Password? First time here? Create an Account. × Login? First time here? Create an Account. × Join our private community on WhatsApp where professionals from FAANG companies share job search tips and tricks based on your area of interest. Software Engineering https://cht.whatsapp.com/software Data Science https://cht.whatsapp.com/data Product Management https://cht.whatsapp.com/product × Struggling to land your dream job? Make The Right Career Move with HiCounselor Career Accelerator Program You don't pay anything until you land a job Our unique strategies have helped thousands of job seekers (just like you!) land a job in software engineering, data science, and product management roles at Apply Now × To continue browsing, sign in with HiCounselor account. Sign in now First time here? Create an Account.
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