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 month, 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. Some of the interesting work done in the team was published in articles such as: (1) Meet Dash-AB-The Statistics Engine of Experimentation at DoorDash, (2) Supporting Rapid Product Iteration with an Experimentation Analysis Platform. We help enable and unlock interesting solutions our product teams use such as (3) The 4 Principles DoorDash Used to Increase Its Logistics Experiment Capacity by 1000%, (4) Improving Online Experiment Capacity by 4X with Parallelization and Increased Sensitivity, etc.
Responsibilities
- Work on dramatically enhancing and simplifying the Experimentation Configuration platform which is used by almost every engineer in the company.
- Build a new Experimentation platform from the ground up and make your mark on the system design as well as product experience.
- Deal with high volume (on the order of 80M QPS) and low latency (on the order of microseconds) evaluations for both experiments and feature flags.
- Develop cutting-edge features with fast iteration and huge impact on the business.
- Collaborate with Product Engineers, Data Analysts, Data Scientists, ML Engineers and Data Infrastructure engineers on important projects that need user interfaces and tools for workflows, data discovery, integrations and visualizations of various analytics.
- Evolve the platform to handle new statistical methodologies, machine learning and artificial intelligence technologies and advanced causal inference and data mining techniques.
Requirements
- B.S., M.S., or PhD. in Computer Science or equivalent.
- 4+ years of industry experience.
- Exceptionally strong knowledge of CS fundamental concepts and OOP languages.
- Deep understanding of REST principles and experience working with and implementing backend APIs.
- Great understanding of database technologies and choosing the right kind of storage layers for the problem at hand.
- Experience with Java/Kotlin/Python/Go-lang/Rust.
- Experience with documentation, unit and integration testing.
Nice-to-haves
- 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.
- Familiar with a cloud based environment such as AWS.
Benefits
- 401(k) plan with an employer match.
- Paid time off.
- Paid parental leave.
- Wellness benefits.
- Paid holidays.
- Paid sick leave in compliance with applicable laws.
- Medical, dental, and vision benefits.
- Disability and basic life insurance.
- Family-forming assistance.
- Commuter benefit match.
- Mental health program.
