DoorDash USA
Machine Learning Engineer, Marketplace Optimization
About this role
Join DoorDash's Marketplace Optimization team to design and deploy machine learning systems powering the ads delivery funnel. You'll build models for bidding, auction design, budget pacing, and forecasting that directly impact advertiser and consumer experiences across a rapidly expanding marketplace.
What you'll do
- Design, build, and deploy ML models and pipelines for pacing, bidding, auction, and targeting optimization
- Collaborate with Data Science and Product teams to develop and evaluate new algorithms through experimentation
- Scale existing ML infrastructure and data pipelines in partnership with Platform and Infrastructure teams
- Execute lift tests and A/B testing frameworks to measure model impact on marketplace KPIs
- Write high-quality, maintainable code and participate in system design and peer reviews
- Partner cross-functionally with engineering, analytics, product, and operations teams
What they're looking for
- Machine learning model design and deployment
- Large-scale data pipeline development
- Deep learning techniques
- Experimentation and A/B testing
- Python or similar ML programming languages
- Software engineering best practices
- Optimization algorithms
- Cross-functional collaboration
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DoorDash USA
DoorDash USA is building autonomous delivery systems including drones and robots, along with internal infrastructure platforms to support large-scale operations. The company is hiring robotics engineers, autonomous systems specialists, infrastructure engineers, and platform software engineers to develop flight control systems, mapping and localization capabilities, and distributed computing platforms.
View all jobs at DoorDash USALikely interview questions
- Walk us through your experience building and deploying ML models to production. How did you handle model monitoring and retraining in a live system?
- Describe a time you optimized an ML pipeline or model for scale. What were the bottlenecks and how did you address them?