Machine Learning Engineer, Marketplace Optimization

DoorDash, Inc

Quick summary

Work type
On-site
Location
San Francisco, CA · Sunnyvale, CA
Salary
$137,100–$201,600 / yr
Posted
1 day ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $211k
This role $169k
$124k most similar roles pay here $261k

This role pays less than 78% of similar roles. Most pay $174,870–$247,875 — the shaded band above. At the midpoint, this role pays about $169k versus about $211k for comparable roles.

Based on 240 similar postings.

Employer

About DoorDash, Inc

DoorDash, Inc. is an American company operating online food ordering and food delivery. It trades under the symbol DASH. With a 56% market share, DoorDash is the largest food delivery platform in the United States.

DoorDash, Inc currently has 238 open roles on FindRole.

Listed pay typically runs $131,600–$193,500 across 156 roles with salary data.

Most-posted roles

View all roles at DoorDash, Inc

At a glance

TL;DR · Machine Learning Engineer, Marketplace Optimization

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As a Machine Learning Engineer at the Marketplace Optimization team within DoorDash, you will design, build, and deploy ML models to optimize ad auctions, bidding strategies, and budget pacing across various verticals. You’ll collaborate with Data Science and Product teams to develop new algorithms through rigorous experimentation and improve existing ML infrastructure in partnership with Platform and Infra teams. Key responsibilities include writing high-quality code, participating in system design reviews, and conducting lift tests with Marketing and Analytics teams. The role requires a strong background in machine learning fundamentals, programming skills in Python or similar languages, and experience with frameworks like TensorFlow or PyTorch. Familiarity with auction systems, bidding, forecasting, and experimentation science is beneficial as you work on one of the largest delivery datasets to enhance marketplace efficiency and fairness.

Skills

Python TensorFlow PyTorch XGBoost Java C++ Kubernetes Docker CI/CD AWS PostgreSQL Auction Systems Forecasting Budget Optimization Experimentation Science ML Frameworks Data Pipelines Machine Learning Infrastructure Large-Scale Data Processing

What you'll do

  • Design and deploy ML models for pacing, bidding, auction, and targeting optimization.
  • Improve and scale existing ML infrastructure in partnership with Platform teams.
  • Write high-quality code and participate in system design and peer reviews.
  • Collaborate on designing and executing lift tests with Data Science and Marketing.
  • Drive experimentation to measure and explain models’ impact on marketplace KPIs.

What we're looking for

  • Industry experience building or maintaining machine learning systems in production.
  • Solid understanding of machine learning fundamentals, statistics, and data modeling.
  • Strong programming skills in Python, Java, or C++, with experience in ML frameworks like TensorFlow.
  • Experience designing and evaluating new algorithms through rigorous experimentation.
  • Ability to improve and scale existing ML infrastructure and data pipelines.
  • Excellent communication and collaboration skills for cross-functional team work.
  • Familiarity with auction systems, bidding, forecasting, or budget optimization is preferred.

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