Machine Learning Engineer - Experimentation Platform
Description For Machine Learning Engineer - Experimentation Platform
DoorDash's Experimentation Platform Team is at the forefront of developing industry-leading platforms for data-driven decision making. The team focuses on enabling Data Scientists, ML Engineers, and non-technical users to design and analyze experiments effectively. As a Machine Learning Engineer, you'll work on cutting-edge experimentation algorithms, partnering with backend and frontend engineers to build platforms that power the company's intelligent delivery system.
The role combines expertise in statistics, machine learning, and engineering to develop sophisticated experimentation methodologies. You'll be responsible for building and evolving platforms that handle advanced statistical methods, ML/AI technologies, and causal inference techniques. The team runs thousands of experiments monthly and has published several technical articles showcasing their innovative work.
Working at DoorDash offers unique opportunities to impact a three-sided marketplace while collaborating with experienced veterans in backend, web, statistical, and data infrastructure engineering. The company provides comprehensive benefits including healthcare, 401(k) matching, parental leave, and equity grants. The position offers competitive compensation ranging from $159,800 to $235,000, based on location and experience.
This role is perfect for someone passionate about the intersection of statistics and machine learning, who wants to work with smart colleagues while building cutting-edge experimentation algorithms. You'll be part of a mission to democratize experimentation and enable data-driven decision-making across the organization.
Responsibilities For Machine Learning Engineer - Experimentation Platform
- Build Experimentation platform with new statistical methodologies, ML and AI technologies
- Drive statistical and ML development of internal platforms including A/B testing, Causal Inference and Adaptive Learning platforms
- Expand statistical and causal inference algorithms for large-scale experimentation
- Apply semi-supervised learning, LLM, active learning, and data augmentation strategies
- Advise data scientists, operators, and engineers on experimental design and tool adoption
Requirements For Machine Learning Engineer - Experimentation Platform
- 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree
- M.S., or PhD. in Statistics, Causal Inference, Experimentation, Computer Science, Applied Mathematics or related quantitative fields
- Demonstrated expertise with programming languages (Python, Java, Kotlin, Go, SciKit Learn, Spark MLLib)
- Located or planning to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA
Benefits For Machine Learning Engineer - Experimentation Platform
- 401(k) plan with employer match
- Paid time off
- Paid parental leave
- Wellness benefits
- Medical, dental, and vision benefits
- Disability and basic life insurance
- Family-forming assistance
- Commuter benefit match
- Mental health program
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