What You'll Do

• Implement a ML framework that includes both model development and robust deployment
• Working with data science and business intelligence, find the data required as model inputs and ensure that it is cleaned and prepared as needed
• Reach out to other teams as needed to get access to data sources; take ownership for following through to ensure that we get the data we need
• Optimize models so that they are cost-efficient when running at scale
• Productionalize models, storing their outputs in accessible formats
• Expose model outputs to applications, whether this means writing database connectors, RESTful APIs, or other types of solutions
• Manage the scheduled retraining of models, working with data science to continually validate outputs

What We're Searching For

• 3-5 years professional experience in a ML Engineering / ML Ops role, or as a data engineer with significant exposure to ML model deployment
• Advanced python skills including significant experience building ML workflows or CI/CD pipelines
• Comfort with data science libraries such as pandas, numpy and scipy
• SQL competence and experience with data cleansing
• Experience optimizing ML models at scale
• Experience working with data scientists to productionalize their models
• Some understanding of hyperparameter tuning and familiarity with common statistical models