ML Engineer: Marketplace Optimization & Bidding

DoorDash; California (MO); Hybrid; USD 137,000 - 299,000; Full time

Job summary

DoorDash is seeking a Machine Learning Engineer to design, build, optimize, and scale large-scale ML systems within the Ads Delivery funnel. You will design, deploy, and evaluate ML models and pipelines for pacing, bidding, auction, and targeting optimization.

You will collaborate with Data Science and Product teams to test new algorithms through rigorous experiments and improve existing ML infrastructure in partnership with Platform and Infra teams.

Qualifications

• BS/MS/PhD in CS/ML/Statistics or related field.
• Experience building machine learning systems in production.
• Strong programming skills in Python/Java/C/C++ and ML frameworks.

Responsibilities

• Design, build, and deploy ML models and pipelines for pacing, bidding, auction, and targeting optimization.
• Collaborate with Data Science and Product teams to evaluate new algorithms via experiments.
• Improve and scale ML infrastructure and data pipelines with Platform and Infra teams.
• Write high-quality code and participate in system design and peer reviews.
• Lead lift tests and PET experiments to measure impact on KPIs.

Skills

ML modeling

Production ML

Python/Java/C/C++

TensorFlow/PyTorch/XGBoost

Education

B.S./M.S./Ph.D. in CS/ML/Statistics

Tools

Claude Code

Codex

Cursor

Job description

DoorDash is seeking a Machine Learning Engineer to design, build, optimize, and scale large-scale ML systems within the Ads Delivery funnel. You will design, deploy, and evaluate ML models and pipelines for pacing, bidding, auction, and targeting optimization.

You will collaborate with Data Science and Product teams to test new algorithms through rigorous experiments and improve existing ML infrastructure in partnership with Platform and Infra teams.