Staff Machine Learning Engineer

• DashPassDashPass is DoorDash'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. DashPass 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 DashPass 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 DashPass and actively engage with their subscription in a personalized way, as well as reduce churn by offering personalized incentives to DashPass 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.

DashPass 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.

About the RoleWe'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 DashPass Subscriber journey.

In this role, you will:

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 01 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.

We're Excited About You Because You HaveM.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 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.

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

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Compensation

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.

DoorDash 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 leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.

To learn more about our benefits, visit our careers page here.

See below for paid time off details:

For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.

For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).

The national base pay ranges for this position within the United States, including Illinois and Colorado.

$1$37,100 - $201,600 USD

$1$67,800 - $246,800 USD

$2$3,500 - $299,300 USD