Machine Learning Engineer - DashPass

San Francisco, CA;
Sunnyvale, CA

Dash Pass is Door Dash’s subscription loyalty program that delivers lower delivery fees and a host of additional benefits and value to a large subscriber base of both paid and sponsored subscriptions. Dash Pass subscribers enjoy lower delivery fees, faster ETAs, 3rd party partnerships, and special discounts and promotions to get maximum value of their membership.

Several teams are part of the Dash Pass org including Growth, Habituation, Member Experience, Exclusive Offers, and Partnerships. All of these teams require personalized targeting of offers and promotions to entice active Doordash consumers to sign up for Dash Pass and actively engage with their subscription in a personalized way, as well as reduce churn by offering personalized incentives to Dash Pass subscribers to keep using their subscription.

We are forming a new team that will leverage AI and advanced ML to power decision making in real-time – from personalized sign up promotions to progressive reward systems, and to pre-cancel offers that retain subscribers.

Dash Pass is continuously building new benefits and offerings to drive more value for our subscribers, and personalization is our next big bet to help efficiently grow our subscriber base to 2030 and beyond.

We’re looking for a Staff Machine Learning Engineer to drive the design and development of large-scale ML/optimization systems to target personalization efforts across the Dash Pass Subscriber journey.

• Contribute to Causal inference modeling to measure the incremental impact of Dash Pass 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 Dash Pass 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.

This is a highly impactful IC role for someone who enjoys combining economic intuition, large‑scale ML modeling, and system design to solve complex real‑world optimization problems.

• 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.
• 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 Tensor Flow, 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.

The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job‑related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market‑dependent and may be modified in the future.

In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.

Door Dash cares about you and your overall well‑being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick…