Staff Machine Learning Engineer - DashPass

DoorDash is a technology and logistics company that empowers local economies. They are seeking a Staff Machine Learning Engineer to design and develop large-scale ML systems aimed at personalizing the DashPass subscriber journey and improving subscriber outcomes.

Responsibilities:

• Contribute to Causal inference modeling to measure the incremental impact of DashPass Subscriber acquisition and retention strategies
• Incentive optimization frameworks that personalize progressive rewards to improve spend efficiency
• Budget allocation and forecasting models that identify optimal spend across acquisition, referrals, and retention
• Partner closely with Product, Data Science, and Engineering teams to design experiments, model frameworks, and production ML systems that directly impact DashPass subscriber growth metrics
• Provide technical mentorship and guidance to engineers and cross-functional partners — leading through influence, not management
• Build and deploy 0→1 ML systems that improve subscriber outcomes and marketplace health
• Set best practices for model training, evaluation, deployment, and monitoring

Requirements:

• M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field
• 8+ years of industry experience building production-scale ML systems
• Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software
• Strong understanding of probability theory, statistics, and machine learning fundamentals
• Strong programming skills in Python, Java, or C++, and experience with ML frameworks such as TensorFlow, PyTorch, or XGBoost
• Interest in building and leading a new team that has broad impact across a wide range of problem spaces to support a critical business line
• Proven ability to lead cross-functional initiatives and drive complex technical projects end-to-end
• Excellent communication skills — able to explain technical concepts to product, business, and engineering audiences
• Experience in subscriptions growth or marketplace systems is a plus