The Experimentation Platform Team at DoorDash is focused on developing an advanced platform that supports Product Engineers, Data Scientists, and ML Engineers in conducting experiments and data analysis. As a full stack engineer, you will work on enhancing the Experimentation platform, building new features, and collaborating with various teams to improve user interfaces and tools. This role offers the opportunity to influence system design and product experience while working under rigorous operational constraints. The position is hybrid, allowing for both in-office and remote work.

• B.S., M.S., or Ph.D. in Computer Science or equivalent.
• 2+ years of industry experience building web applications end-to-end, using TypeScript with React on the frontend.
• Exceptionally strong knowledge of CS fundamental concepts and OOP languages.
• Deep understanding of REST/gRPC principles and experience designing, implementing, and consuming backend APIs.
• Great understanding of database technologies and choosing the right kind of storage layers for the problem at hand.
• Backend experience with Java, Kotlin, Python, or Go.
• Experience with documentation, unit, integration, and end-to-end testing across frontend and backend.
• A product mindset that you apply to how you build platform services and user-facing tools.
• Proficiency in using AI coding tools across the full software development lifecycle.

• Work on dramatically enhancing and simplifying the Experimentation platform used by engineers in the company.
• Build a new Experimentation platform from the ground up and influence system design and product experience.
• Own features end-to-end, from APIs and data models to the React UI in the Decision Portal.
• Collaborate with Product Engineers, Data Analysts, Data Scientists, ML Engineers, and Data Infrastructure engineers on important projects.
• Introduce cutting-edge technologies into how DoorDash configures, launches, and reads out experiments.
• Evolve the platform to handle new statistical methodologies and advanced data analysis techniques.