Software Engineer, Full Stack - Experimentation Platform

DoorDash USA•Los Angeles, CA

2d•$130,600 - $192,000•Hybrid

About The Position

The Experimentation Platform Team develops a state-of-the-art platform in industry that enables Product Engineers, Data Scientists, ML Engineers and non-technical audiences to come up with hypotheses; design, configure and analyze experiments; and conduct exploratory and causal analysis. At DoorDash, where we run thousands of experiments per year, our mission is to equip all decision makers with rigorous, data-driven insights by democratizing experimentation with quality and velocity. The team consists of a mix of experienced veterans of backend, web, statistical and data infra engineers and work closely with the data science community. If you want to solve the toughest engineering challenges, build cutting-edge experimentation products under rigorous operational constraints (high volume, correctness guarantees) and work with some of the smartest people in the industry, DoorDash’s Experimentation Platform is the right place for you. As a full stack engineer, you’ll build across our backend services, SDKs, and the Decision Portal UI used by thousands of internal users. Come join us and be part of the mission. You will report into the engineering manager on our Decision Experience team as part of the Decision Systems team. We expect this role to be hybrid (San Francisco, Sunnyvale, Seattle, New York) with some time in-office and some time remote.

Requirements

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 (e.g., Claude Code, Codex, Cursor) across the full software development lifecycle, including design, code generation, testing, monitoring, and release.

Nice To Haves

Experience building internal tools, admin consoles, or developer platforms used across many teams.
Prior experience with the nuanced world of Experiment configurations and feature flagging products.
Experience with any of the “Big Data” technologies (e.g., Postgres, Redis, Elasticsearch, Snowflake, Mode, Segment, Spark, etc.).
Experience in any data-science related subjects such as analytics, statistics, machine learning, etc.
Familiarity with cloud-based environments such as AWS.

Responsibilities

Work on dramatically enhancing and simplifying the Experimentation platform which is used by almost every engineer in the company.
Have the opportunity to build a new Experimentation platform from the ground up and make your mark on the system design as well as product experience.
Own features end-to-end, from APIs and data models to the React UI in our Decision Portal, context switching between frontend, backend, and data as the need arises.
Work alongside our Product Engineers, Data Analysts, Data Scientists, ML Engineers and Data Infrastructure engineers to collaborate on important projects that need user interfaces and tools needed for workflows, data discovery, integrations and visualizations of various analytics.
Introduce cutting-edge technologies, including LLM-powered tools, into how DoorDash configures, launches, and reads out experiments.
Evolve the platform to handle new statistical methodologies, machine learning and artificial intelligence technologies and advanced causal inference and data mining techniques.