Machine Learning Engineer, Marketplace Optimization
DoorDash · San Francisco, CA | Sunnyvale, CA · 341 Executive Engineering
About this role
DoorDash is hiring a mid-level Machine Learning Engineer based in San Francisco, CA | Sunnyvale, CA. The posting calls out experience with Python, Java, TensorFlow, PyTorch. Compensation is listed at $137,100–$201,600 per year.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Francisco, CA | Sunnyvale, CA
- Department
- 341 Executive Engineering
More roles at DoorDash
Job description
from DoorDash careers
About the Team
The mission of the Marketplace Optimization team is to ensure we maintain a healthy Ads Marketplace across all our verticals for both search (query context) and discovery experiences while fulfilling the requirements of all players in this marketplace.
Marketplace Optimization is a critical part of the Ads Delivery funnel with a broad charter responsible for Bidding, Auction Design, Budget Pacing, Forecasting, and Ads Experimentation. Our work directly shapes advertiser experience, consumer experience, and marketplace balance. We leverage artificial intelligence and advanced ML, deep learning techniques to power decision-making in real time — from optimizing ad auctions to generating the most efficient bids and pacing budgets dynamically. These models sit at the heart of DoorDash’s ad delivery and play a pivotal role in improving the efficiency, fairness, and scalability of our marketplace.
The opportunity is massive as DoorDash expands into new verticals like Grocery and Retail while building unique innovative ad products to leverage the closed loop marketplace.
About the Role
We’re looking for a Machine Learning Engineer to help design, build, optimize and scale large-scale ML systems within the Ads Delivery funnel.
- Design, build, and deploy ML models and pipelines for pacing, bidding, auction and targeting optimization.