Machine Learning Job Description

Machine Learning Job Description

197 votes for Machine Learning
Machine learning provides extensive trainings and workshops for new hires/experienced roles in tech about testing culture and best practices.

Machine Learning Duties & Responsibilities

To write an effective machine learning job description, begin by listing detailed duties, responsibilities and expectations. We have included machine learning job description templates that you can modify and use.

Sample responsibilities for this position include:

Work within the Machine Learning Team to design, code, train, test, deploy and iterate on large scale machine learning systems
Conduct original research in Machine Learning for application in computer vision, natural language processing, security, privacy and HCI
Teach team members about latest developments in Machine Learning
Implementing scalable, efficient machine learning algorithms on a variety of platforms with product-level quality
Identifying opportunities to leverage machine learning in innovative ways in the system
Conduct experiments for evaluation of various machine learning technologies
Implement “industrial strength” cognitive systems requiring machine learning, natural language processing, advanced analytics, or other sophisticated mathematical components
Lead the implementation and testing of these solutions as an active (hands-on) part of a small multi-disciplinary team
Further the understanding of machine learning and cognitive tools internally at Indellient as part of the advanced analytics team
Lead and grow a team of expert machine learning engineers

Machine Learning Qualifications

Qualifications for a job description may include education, certification, and experience.

Licensing or Certifications for Machine Learning

List any licenses or certifications required by the position: AWS, PMP, GPEN, CEH, CISSP, PMI, SQS, SNS, S3, ISTQB

Education for Machine Learning

Typically a job would require a certain level of education.

Employers hiring for the machine learning job most commonly would prefer for their future employee to have a relevant degree such as Master's and Bachelor's Degree in Computer Science, Mathematics, Machine Learning, Engineering, Statistics, Graduate, Electrical Engineering, Technical, Science, Physics

Skills for Machine Learning

Desired skills for machine learning include:

Code reviews
Build processes
Source control management
Professional software engineering practices & best practices for the full software development life cycle
Machine learning

Desired experience for machine learning includes:

Demonstrated research experience in the field of Machine Learning, Mathematical Modeling, Computer Science, and Advanced Cyber Security Research
Delivered models in high-stakes information retrieval and statistical analysis, Bioinformatics, Fraud Detection, Education
Design lean proofs of concepts (POC) to answer targeted business questions
You will be relied upon for technical leadership in this role
Engage in data analysis in a practical way
You'll need an Advanced Degree in Computer Science, Statistics, Math, Engineering, or another quantitative discipline

Machine Learning Examples


Machine Learning Job Description

Job Description Example
Our company is growing rapidly and is searching for experienced candidates for the position of machine learning. Please review the list of responsibilities and qualifications. While this is our ideal list, we will consider candidates that do not necessarily have all of the qualifications, but have sufficient experience and talent.
Responsibilities for machine learning
  • Solve challenging problems in varied fields such as personalization/customer data analytics, resource optimization/operations research, natural language processing, computer vision and multi-source fusion of machine sensor data
  • Take responsibility for ensuring that our code, models and pipelines are deployed successfully into operations, and troubleshooting issues that arise
  • Perform literature reviews in areas of focus and present state-of-the-art findings to the team
  • Formulate and test hypotheses fast and efficiently and Draft, edit and publish academic papers in leading scientific conferences
  • Participate and present work in academic conferences
  • Accountable for the accurate documentation and presentation of technical information to the team and accountable for the accurate and thorough consideration of security, privacy or other technical issues related to technologies
  • Collaborate with RBC’s data scientists over the use of novel ML algorithms for data analytics and collaborate with development team to enable the transfer of research results into demoable applications
  • Interfacing with customers, learning from their feedback, implementing their suggestions and quickly deploying new, improved versions
  • Conducting technical investigation and prototyping in a fast-paced environment
  • 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
Qualifications for machine learning
  • Familiarity with machine learning packages Weka, R, Scikit-learn, Scala/Spark, Mahout, Vowpal Wabbit
  • 2-4+ years relevant work experience in data analysis
  • Must be proficient in Python, R, C++ or MATLAB
  • Must be proficient with some analysis language or library (e.g.scikit-learn, NumPy, R, MATLAB, SciPy)
  • Deep theoretical knowledge and hands-on experiences in speech recognition, natural language understanding and machine learning
  • Methodology selection

Machine Learning Job Description

Job Description Example
Our innovative and growing company is searching for experienced candidates for the position of machine learning. Please review the list of responsibilities and qualifications. While this is our ideal list, we will consider candidates that do not necessarily have all of the qualifications, but have sufficient experience and talent.
Responsibilities for machine learning
  • You will bring active experience in Machine Learning into the organization and knows the techniques to build indexes, normalize data, get features out of PDFs and Xml files alike, select algorithms and rule mechanisms that are necessary to capture the information desired from unstructured data
  • Use machine learning algorithms to develop useful and accurate computer vision tasks
  • Develop software aided decision support solutions through ICT and Machine learning to support Industry 4.0
  • Gatekeep Machine Learning trends and technologies in order to propose relevant projects and solutions
  • Apply machine learning technique to provide insight and foresight into
  • Develop and provide input for a hybrid predictive analytics and machine learning solution spanning both IoT devices and data center systems
  • Collaborate to improve user experiences with the aid of machine learning and predictions
  • Prototype new technologies in areas such as natural language processing, reinforcenemtn learning, deep learning and visualization
  • Participate in research projects by assisting in data collection, algorithm implementation, simulation and publication
  • Provide technical guidance in ML experiments and projects
Qualifications for machine learning
  • Expertise with cross-compiling open source software for target architectures (ARM, etc)
  • Knowledge of Computer Architecture (ARM/Intel)
  • Extensive experience with compilers, debuggers
  • Experience with Python for Android development (Kivy, making patches for existing python packages including numpy, hdf5, etc)
  • Knowledge of any deep learning framework (Theano, Tensorflow, Caffe, Torch)
  • Take pride in the code that they write – quality first!

Machine Learning Job Description

Job Description Example
Our company is growing rapidly and is looking to fill the role of machine learning. If you are looking for an exciting place to work, please take a look at the list of qualifications below.
Responsibilities for machine learning
  • Partner with other teams such as Design and Product to collaborate on projects across the customer service
  • Work with the engineering management team to develop new initiatives and improve existing processes across the entire engineering team
  • Work closely with Recruiting to expand the team, including sourcing candidates, interviewing candidates, participating in conferences/events, and on-boarding new employees
  • Build/verify ML models that can handle noise (build models robust enough handle to varying quality of data provided by millions of customer contacts derived implicitly or collected from humans)
  • Work on public/private banks of data used to evaluate the various models
  • Tailor the models for mobile devices, cooperation with SW/HW engineers
  • Cooperation with our teams in different countries
  • Recruit, coach, and manage a team of scientists and data science engineers, lead cutting-edge research projects, and influence the technical direction of the Ads business
  • Work with our engineering team to establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
  • Formulate and test hypotheses, extract signals from peta-byte scale, unstructured data sets, and ensure that our display advertising business delivers the highest standards of performance
Qualifications for machine learning
  • An in-depth understanding of machine learning algorithms and modeling
  • 5+ years of professional experience in machine learning, mathematical modeling, statistical modeling, optimization or data mining involving large data sets
  • Ideally have professional experience in a financial services related industry (e.g., banking and securities, asset management, insurance)
  • At least 2 years of experience with current data visualization applications and tools
  • Master’s or PhD degree in a quantitative field such as statistics, math, applied mathematics, financial mathematics
  • In depth understanding of risk measurement frameworks, including the ability to identify and communicate risk concentrations and key drivers of risk and capital via presentations or reports

Machine Learning Job Description

Job Description Example
Our company is hiring for a machine learning. To join our growing team, please review the list of responsibilities and qualifications.
Responsibilities for machine learning
  • Supports other teams by advocating a testing first strategy to integrate A/B testing into all levels of product development
  • Conduct original research in specific Machine Learning areas of interest
  • Work with development mentors and colleagues to both implement and develop from scratch new Machine Learning algorithms and approaches
  • Evaluate, revise, and improve Machine Learning systems based on quantitative metrics feedback and suggestions from colleagues
  • Collaborate with distributed cross-functional teams on common goals
  • Additionally, you will have to deploy production deep nets on the FPGA in the area of image classification, language parsing, and object localization
  • Create State Space modeling methods for Thermal Performance models
  • Deploy Deep Learning environments for applications using multi-layer neural networks
  • Create event labeling database using NLP and Deep Learning
  • Build a framework for deploying a training dataset that combines events with sensor data
Qualifications for machine learning
  • Working knowledge of Generally Accepted Accounting Principles (GAAP), Basel III, Dodd-Frank Act Stress Testing, and bank accounting/regulatory reporting requirements
  • CFA, PRM, or FRM designation or candidate
  • Required experience in R, Python and/or Tensorflow
  • Applied Machine Learning modeling expertise is required
  • Background in Deep Learning (CNN, LSTM), Natural Language Processing (Word2Vec), and Anomaly Detection is highly preferred
  • Desired experience in Java, PHP, J#.Net environment, Perl, Mathematica, MATLAB, Hadoop, Spark, SAS, STATA, SPSS, RapidMinder, S-plus, ARC-GIS, Weka, NetLogo, MASON, RePast

Machine Learning Job Description

Job Description Example
Our company is hiring for a machine learning. Please review the list of responsibilities and qualifications. While this is our ideal list, we will consider candidates that do not necessarily have all of the qualifications, but have sufficient experience and talent.
Responsibilities for machine learning
  • Contribute to the methodology for handling mathematical expressions in submitted scientific articles
  • Contribute to a software library for handling math in submitted articles
  • Using the available base data, you will actively promote new ideas of using this data to enhance our competitive offerings
  • You will also need to act as a liaison between IT developers and (content) subject matters experts, translating information needs into software development
  • Communicate with key global stakeholders (production, Group IT etc) to develop the right solutions for the SKF manufacturing arena
  • Further develop the existing Advanced Analytics Software and introduce to other machines and systems
  • Develop visualization tools and Quality prediction systems for Quality Technology
  • Work close together with Universities
  • Create a data collection and analytics solution to build a training corpus from real world systems to enable future learning capabilities
  • Established program, committed resources, an involved supervisor or mentor
Qualifications for machine learning
  • Desired experience using other programming and data manipulation languages (SQL, Hive, Pig, C/C++)
  • Solid MS Office skills - Excel (including macros and VBA) and Access (or SQL), storyboarding and PowerPoint at high proficiency preferred
  • Knowledge of any one visualization tool such as Tableau, Spotfire, PowerView, QlikView, D3.js or equivalent
  • Experience in developing advanced models such as multivariate regression, neural networks, support vector machines, Random Forest, Bayesian Analysis, decision trees, ANOVA
  • Well-honed analytical problem-solving ability coupled with business acumen to structure problems, deliver solutions and communicate insights
  • Strong quantitative and conceptual thinking skills, with attention to detail and accuracy

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