Machine Learning Engineer, Marketplace Optimization

DoorDash DoorDash · Consumer · San Francisco, CA · 341 Executive Engineering

Machine Learning Engineer focused on optimizing DoorDash's Ads Marketplace. This role involves designing, building, and deploying ML models and pipelines for critical functions like pacing, bidding, auction, and targeting. The engineer will collaborate with Data Science and Product teams, improve ML infrastructure, and ensure models are production-ready and scalable, directly impacting financial metrics and marketplace efficiency.

What you'd actually do

  1. Design, build, and deploy ML models and pipelines for pacing, bidding, auction and targeting optimization.
  2. Collaborate with Data Science and Product teams to develop and evaluate new algorithms through rigorous experimentation.
  3. Improve and scale existing ML infrastructure and data pipelines in partnership with Platform and Infra teams.
  4. Write high-quality, maintainable code and participate in system design and peer reviews.
  5. Learn from senior engineers and contribute to technical discussions that shape the team’s roadmap.

Skills

Required

  • Python
  • Java
  • C++
  • TensorFlow
  • PyTorch
  • XGBoost
  • machine learning fundamentals
  • statistics
  • data modeling
  • communication skills
  • collaboration skills

Nice to have

  • auction systems
  • bidding
  • forecasting
  • budget optimization
  • ads or marketplaces
  • experimentation science
  • lift tests
  • marketplace incrementality

What the JD emphasized

  • large-scale ML systems
  • optimize at scale
  • models that directly have a large impact on top and bottom line financials
  • robust sequential experiments
  • building optimization pipelines

Other signals

  • ML models and pipelines for pacing, bidding, auction and targeting optimization
  • optimize large-scale ML systems
  • optimize at scale
  • move models from prototype to production