Machine Learning Engineer
September 14
Description
• 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
Requirements
• 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
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