DoorDash is looking to build the world's most reliable on-demand logistics engine and improve company-wide ML workflows such as Search & Recommendations, Catalog building, Fraud intelligence, Chatbot intelligence.
Requirements
- Strong fundamentals in computer science and Python
- Experience building and deploying machine learning systems in production
- Hands-on ML experience, including developing and testing your own models (even simple ones)
- Experience building infrastructure in cloud environments—especially backend services and data pipelines at scale
- Experience fine-tuning and serving open-weights LLMs in production
- Experience building and deploying AI agents in production
- Experience in cloud environments like AWS or GCP
Responsibilities
- Use your backend, data, and ML infrastructure expertise to help build a high-quality GenAI platform.
- Build scalable, high-performance data and ML pipelines—from retrieval (e.g., RAG) to batch inference—that adapt quickly to new technologies.
- Develop an easy-to-use platform that supports fast iteration and deployment of products powered by Generative AI.
- Improve the reliability, scalability, and monitoring of our GenAI infrastructure, including the LLM gateway, fine-tuning systems, and model serving.
- Collaborate with ML Engineers and Product Engineers to evolve the ML platform as per their use cases.
- Shape the direction of DoorDash's centralized ML platform that supports all business functions.
Other
- B.S., M.S., or PhD. in Computer Science or equivalent
- 4+ years of industry experience in software engineering
- Travel requirements not specified, but remote opportunity with Pacific Time working hours requirement
- Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only
- Comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more
