ML Engineer — Marketplace Optimization & Bidding

Visa Hunt; San Francisco, Sunnyvale (CA, CA); On-site; USD 137,000 - 299,000; Full time

Benefits offered by this job

401(k) matching

Health benefits

Paid parental leave

Job summary

DoorDash in San Francisco is seeking a Machine Learning Engineer to design, scale, and optimize large‑scale ML systems within the Ads Delivery funnel. You will build models for pacing, bidding, auction and targeting optimization, and collaborate with Data Science and Product teams to test new algorithms through rigorous experiments.

You’ll work with data platforms and engineering partners to improve pipelines, write high‑quality code, and push production readiness.

Qualifications

• BS/MS/PhD in CS, ML, or a related field.
• Experience building or maintaining production ML systems.
• Strong Python/Java/C++ programming skills.
• Familiarity with ML frameworks (TensorFlow, PyTorch, XGBoost).

Responsibilities

• Design, build, and scale ML models and data pipelines for pacing, bidding, and targeting optimization.
• Collaborate with data science and product teams to evaluate new algorithms via experiments.
• Improve ML infrastructure and data pipelines with platform and infra teams.
• Write maintainable code and contribute to system design and peer reviews.

Skills

Python

Java or C++

ML frameworks

Production ML systems

Communication

Experiment design

Auction/bidding knowledge

Education

Bachelor's/Master's/PhD in CS/ML

Tools

TensorFlow

PyTorch

XGBoost

Job description

DoorDash in San Francisco is seeking a Machine Learning Engineer to design, scale, and optimize large‑scale ML systems within the Ads Delivery funnel. You will build models for pacing, bidding, auction and targeting optimization, and collaborate with Data Science and Product teams to test new algorithms through rigorous experiments.

You’ll work with data platforms and engineering partners to improve pipelines, write high‑quality code, and push production readiness.