Principal Machine Learning Engineer

Chewy - Boston, MA

Full-time - Principal

Boston, MA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

As a Principal Machine Learning Engineer at Chewy, you will play a pivotal role in transforming customer experiences through innovative machine learning models. The Chewy Search & Recommendations team is dedicated to simplifying product discovery for pet owners on Chewy.com. This multi-disciplinary team, comprising data scientists, data engineers, software engineers, and product managers, collaborates to create personalized recommendations and search functionalities that cater to the needs of pet parents. Your contributions will directly impact millions of customers, making their shopping experience more intuitive and frictionless. In this position, you will be involved in all stages of model development, from ideation and analysis to architecture, pipeline creation, tuning, experimentation, and establishing feedback loops. You will have the opportunity to work on significant science projects, taking them from concept through offline evaluation to deployment, experimentation, and continuous model improvement. Your role will also include formalizing assumptions about model behavior, defining outliers, and developing systematic methods to identify and address these outliers. You will be expected to present your findings and insights to business stakeholders with varying levels of technical expertise, ensuring that your research translates into actionable business recommendations. The team values collaboration and learning, and you will work alongside passionate individuals who are committed to advancing data science and machine learning techniques. This position offers the chance to make a tangible impact on the business while working in a supportive and innovative environment.

Responsibilities

• Partner with peer Machine Learning Engineers, Program Managers, and Merchandising teams to drive science projects.
• Manage science projects from idea conception to offline evaluation, deployment, experimentation, and feedback.
• Formalize assumptions about model behavior and craft definitions of outliers.
• Develop methods to systematically identify outliers and provide explanations or fixes for them.
• Present research findings and insights to business customers with varying technical knowledge levels.
• Collaborate with a team of data science and machine learning professionals to enhance modeling techniques.

Requirements

• An advanced degree (Undergrad, M.S. or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data Science, or a related field, or 10+ years of proven experience in crafting optimization and machine learning solutions for large-scale applications.
• Strong understanding and application of sophisticated mathematics and data science methodologies.
• Experience in building distributed pipelines, tuning, optimizing, and evaluating models.
• Proficiency in various predictive modeling techniques, including Time Series, Regression, Linear models, NLP/NLU, Search, Ranking, and LLM & generative AI.
• Ability to translate complex data sets and research into simple business recommendations.
• Experience mentoring and growing junior data science team members.

Nice-to-haves

• Experience in e-commerce or retail environments.
• Familiarity with ML Services in AWS (SageMaker, Personalize) or equivalent platforms.