Machine Learning Engineer III

3 weeks ago

Boston, United States Chewy Full time
JOB DESCRIPTION

Our Opportunity:

Do you want to build a model that impacts the company's bottom line? Do you want to see how your ideas, pipelines, architecture, and experiments affect top-level decision-makers? If so, the Chewy Marketing & Science team is hiring We use the best machine learning techniques to simplify product discovery for pet parents looking for their pet needs on Chewy.com. The team uses machine learning, statistics, and business econometrics techniques to understand and serve the needs of our pet parents. As part of the Marketing Science teams, you will have ample opportunities to solve numerous business problems for marketing and existing Chewy customers. Our team has single-threaded ownership to make data science products powered by econometric models, causal inference, forecasting, and non-linear optimization. We are hiring a  Machine Learning Engineer III  in Bellevue, WA, Boston, MA, or Plantation, FL. In this position, you will work on all stages of model development, from idea, analysis, architecture, pipeline, tuning, experimentation, and feedback loop. This team's MLEs and data scientists focus on learning and working together to deploy the model to production and advance our modeling technique. Join our high-achieving team

What You’ll Do:

You will partner with peer MLEs, Program Managers, Marketers, Finance, and top engineers at Chewy.  You will be responsible for science projects from idea to offline evaluation to deployment, to experiment, to feedback, to model improvements for not only your science projects.  Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to identify them systematically, and explaining why they are reasonable or identifying fixes.  Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, and sharing insights and recommendations. Work with a team of incredible people passionate about data science, machine learning, search & personalization.

What You’ll Need:

An advanced degree (undergraduate, M.S. or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Physics, Data Science, or a related field or 4+ years' experience designing optimization and machine learning solutions for large-scale applications.  Ability to understand and apply advanced mathematics and DS methodologies.  Experience in building distributed pipelines, tuning, optimizing, and evaluating. Experience in MLOps best practices and demonstrated use of Software Engineering best practices.  Experience with techniques including Predictive Models (Time Series, Regression, etc.). Ability to translate complex data sets and research into simple business recommendations. 

Bonus (if applicable):

Experience with causal inference. If not, we'll teach you. Experience with at least one cloud services provider(AWS, GCP, Azure, etc.). Experience with a back-end framework (Flask, Fast API, Django, Spring, etc.). Experience with ML/DE framework, e.g., Databricks.

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