About the Team

DoorDash is building the world’s most reliable on-demand logistics engine. Behind the scenes, our Machine Learning Platform (MLP) powers critical real-time decision-making for millions of orders each day, supporting business-critical use cases like Groceries, Logistics, Fraud, Search and Personalization.

About the Role

At DoorDash, our Data Scientists and ML Engineers have the opportunity to dive into a wealth of delivery data to improve company-wide ML workflows such as Search & Recommendations, Catalog building, Fraud intelligence, Chatbot intelligence. You will join a small team to build systems that empower efficient machine learning at scale, especially in the Generative AI area. This is a remote opportunity, with Pacific Time working hours requirement.

You’re excited about this opportunity because you will…

• 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.

We’re excited about you because…

• B.S., M.S., or PhD. in Computer Science or equivalent
• Strong fundamentals in computer science and Python
• 4+ years of industry experience in software engineering
• 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

Nice To Haves

• Experience fine-tuning and serving open-weights LLMs in production
• Experience building and deploying AI agents in production
• Experience building and deploying MCP servers in production
• Experience in cloud environments like AWS or GCP

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

Compensation

The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions.  Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.

In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.

DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.

To learn more about our benefits, visit our careers page here.

See below for paid time off details:

• For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
• For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/