DoorDash
Consumer · Delivery
- HQ
- San Francisco, US
- Founded
- 2012
- Website
- doordash.com
DoorDash is actively hiring for 28 AI-related roles. The majority of these positions, 61%, are focused on agents, with application roles making up another significant portion at 29%. Engineering is the primary function for these hires. Frequent tech tags include model serving, agent orchestration, and recommender systems, suggesting a focus on deploying and managing AI models for user-facing applications.
Currently tracking 12 active AI roles, down 23% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $102k–$395k (avg $228k).
Consumer · Delivery
DoorDash currently has 29 active AI-related roles in our index. The most common open titles are: Software Engineer, Infrastructure - Autonomy & Robotics (2), AI Research Fellowship, (Summer and Fall 2026), Associate, Fraud Insights Operations, Director of Engineering, Logistics, Director, Ads Platform Strategy & Operations, Ads & Promotions. Most positions are in Engineering and Product.
DoorDash's active AI hiring is concentrated in: agents (66%), application (24%), serving infrastructure (7%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
DoorDash is hiring AI talent in: United States (29 roles).
Job postings at DoorDash most frequently reference: agent orchestration, model serving, recommender systems, rag, search ranking.
In the past 30 days, DoorDash has posted 9 new AI-related roles. That is a +29% change versus the prior 30 days (7 → 9).
| Title | Stage | AI score |
|---|---|---|
| Director of Engineering, Logistics Director of Engineering for DoorDash's Logistics Org, leading 100+ engineers across Backend, Mobile, ML, and Operations Research. The role focuses on architecting intelligent, real-time systems, optimization engines, and high-throughput AI platforms for fulfillment, dispatching, dynamic pricing, ETAs, and supply-demand balancing. Key responsibilities include defining AI/Platform vision, architecting real-time decision engines, building production-grade ML, scaling infrastructure, and cross-functional leadership. | ServeAgent | 8 |
| Machine Learning Engineer - ETA Team Machine Learning Engineer to develop and improve ETA models for DoorDash's logistics engine. The role involves building deep learning models for time predictions, owning the modeling lifecycle end-to-end, and shipping production-grade ML models and optimization systems. | Serve | 7 |