Machine Learning Job Description
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:
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:
Desired experience for machine learning includes:
Machine Learning Examples
Machine Learning Job Description
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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