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 Ads, Groceries, Logistics, Fraud, and Search.

About the Role

At DoorDash, the Frontend Engineer on the ML Infrastructure team builds intuitive, high-impact tools that accelerate machine learning across the company. You'll create user interfaces that support core ML workflows—like model training, experiment tracking, and Generative AI development—empowering teams working on Search, Recommendations, Fraud, Chatbots, and more. ML experience is not required—this is a perfect opportunity to learn AI/ML and Generative AI by working alongside top experts in the field. You must be located in San Francisco, Sunnyvale, or Seattle for this hybrid position. 

You’re excited about this opportunity because you will… Work at the intersection of engineering and AI by building tools that power machine learning across DoorDash. Collaborate with top ML engineers and researchers, gaining hands-on exposure to cutting-edge AI workflows—no prior ML experience required. If you are keen to learn ML, the team is ready to help you! Own high-impact frontend systems that directly influence the speed, scale, and reliability of model development and deployment. Solve complex UI/UX challenges in technical domains like model experimentation, data visualization, and ML observability. Join a small, high-leverage team where your contributions shape the future of DoorDash’s ML platform. We’re excited about you because… 5+ years of experience building and maintaining production-grade frontend applications Proficiency in modern JavaScript/TypeScript and frontend frameworks, especially React Strong understanding of UI/UX principles and ability to build intuitive user interfaces Experience integrating with REST/gRPC APIs and a solid grasp of fullstack fundamentals, including backend interaction patterns and data flow Comfortable collaborating with backend, ML, and infrastructure teams to define and consume data endpoints in Python backend services. Familiarity with GenAI coding tools like Cursor Nice To Haves Familiarity with ML workflows, experiment tracking, or model management tools Background in building developer tools or internal platforms at scale Experience in cloud environments like AWS or GCP

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