华人工作网 · 返回最新招聘
doordashusa

Software Engineer, Full Stack - Experimentation Platform

San Francisco · CA · 发布于 2026-10-07
<div class="content-intro"><p><img style="display: none; max-width: 100%;" src="https://click.appcast.io/greenhouse-te8/a31.png?ent=34&amp;e=22630&amp;t=1701374353806" width="1px"> <img style="display: none; max-width: 100%;" src="https://track.jobadx.com/v1/i.gif?utm_pixel=224e990b-8ff4-4287-8d5d-2ff09647f181&amp;utm_ptz=EST&amp;utm_rqt=track" alt="" width="1"></p></div><h2>About the Team</h2> <p>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.</p> <p>Some of the interesting work done in the team was published in articles such as:</p> <ul> <li><a href="https://doordash.engineering/2022/05/24/meet-dash-ab-the-statistics-engine-of-experimentation-at-doordash/">Meet Dash-AB-The Statistics Engine of Experimentation at DoorDash</a></li> <li><a href="https://doordash.engineering/2020/09/09/experimentation-analysis-platform-mvp/">Supporting Rapid Product Iteration with an Experimentation Analysis Platform</a></li> <li><a href="https://doordash.engineering/2021/09/21/the-4-principles-doordash-used-to-increase-its-logistics-experiment-capacity-by-1000/">The 4 Principles DoorDash Used to Increase Its Logistics Experiment Capacity by 1000%</a></li> <li><a href="https://doordash.engineering/2020/10/07/improving-experiment-capacity-by-4x/">Improving Online Experiment Capacity by 4X with Parallelization and Increased Sensitivity</a></li> </ul> <h2>About the Role</h2> <p>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.</p> <p>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.</p> <h2>What You'll Do</h2> <ul> <li>Work on dramatically enhancing and simplifying the Experimentation platform which is used by almost every engineer in the company.</li> <li>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.</li> <li>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.</li> <li>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.</li> <li>Introduce cutting-edge technologies, including LLM-powered tools, into how DoorDash configures, launches, and reads out experiments.</li> <li>Evolve the platform to handle new statistical methodologies, machine learning and artificial intelligence technologies and advanced causal inference and data mining techniques.</li> </ul> <h2>What We're Looking For</h2> <ul> <li>B.S., M.S., or Ph.D. in Computer Science or equivalent.</li> <li>2+ years of industry experience building web applications
前往雇主官网申请
联系前请核实雇主身份、工作地点、薪资和用工条件;不要向陌生人提供银行卡密码或验证码。