Staff Machine Learning Engineer

Chewy Chewy · Retail · Bellevue, WA

Staff Machine Learning Engineer at Chewy focused on Sponsored Ads. The role involves deploying ML and data science models to improve shopping experience, selection, ranking, relevance, click-through prediction, bidding, and auction algorithms for onsite and offsite advertising solutions. Key responsibilities include leading models from ideation to production, publishing research, establishing best practices, and mentoring junior scientists. Requires experience in building distributed pipelines, tuning, optimizing, and evaluation, with a background in Sponsored Ads or Advertisement domain, and techniques like predictive models, linear programming, classification, search, ranking, or large-scale embeddings.

What you'd actually do

  1. You will deploy machine learning and data-science to simplify shopping experience for pet-parents, to maximize reach and discovery of new products of Chewy vendors and helping create a win-win ecosystem.
  2. Directly influence and collaborate with Product and Engineering leaders to evolve solutions using applied science to improve selection, ranking, relevance, deal-offerings, click through prediction models, dynamic bidding, and auction algorithms for Chewy onsite and offsite advertising solutions.
  3. You will lead new models from ideation to experimentation, and eventually to production delivery to improve Chewy products offerings and advance applied science applications.
  4. Publish research papers in leading ML/AI/Advertising conferences solving problems for scale using innovative modelling.
  5. Establish high bar on model performance, establish applied-science implementation best practices and mentoring junior scientists.

Skills

Required

  • advanced degree (M.S., PhD, or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data Science or related field or proven experience for at least 3 years designing optimization and machine learning solutions for large scale applications
  • Ability to understand and apply sophisticated mathematics and DS methodologies
  • Experience in building distributed pipeline, tuning, optimizing and evaluation
  • Experience with Sponsored Ads or Advertisement domain
  • Experience with multiple techniques that include Predictive Models (Time Series and Regression), Linear Programming, and Classification, Search, Ranking or large-scale embeddings
  • Ability to translate complex data sets and research into simple business recommendations

Nice to have

  • Experience in e-commerce or retail
  • Prior experience in Advertising systems a huge plus
  • Experience with ML Services in AWS (SageMaker, Personalize) or equivalent

What the JD emphasized

  • Sponsored Ads
  • advertisement domain
  • large scale applications
  • large selection
  • large-scale embeddings

Other signals

  • deploy machine learning and data-science
  • improve selection, ranking, relevance, deal-offerings, click through prediction models, dynamic bidding, and auction algorithms
  • lead new models from ideation to experimentation, and eventually to production delivery
  • Deploy solutions at Chewy scale