About the Role

We're seeking a Machine Learning Engineer to lead the development of state-of-the-art ML systems that personalize and optimize credits and refund decisions. This work is critical to balancing cost efficiency with long-term customer retention and experience.

In this high-impact role, you will partner with cross-functional leaders to design and deploy causal models and optimization algorithms that influence millions of user experiences every week.
You're excited about this opportunity because you will...

• Designing and deploying causal inference models to accurately assess the impact of refunds and credits on customer satisfaction, retention, and behavior
• Developing optimization frameworks that balance customer experience with operational cost, under policy and budget constraints
• Building personalized decision systems that adapt to customer preferences and platform dynamics in real time
• Collaborating with engineering, product, and data science partners to shape the roadmap for trust, service recovery, and consumer experience
• Leading end-to-end model development, including experimentation, deployment, monitoring, and iteration

We're excited about you because you have:

• 3+ years of industry experience delivering machine learning systems with clear business impact, especially in personalization, optimization, or causal inference
• Deep expertise in statistical modeling and causal inference (e.g., uplift modeling, treatment effect estimation, synthetic controls, instrumental variables)
• Experience designing and deploying optimization algorithms (e.g., multi-objective optimization, bandits, constrained optimization)
• Proficiency in Python and ML tooling such as PyTorch, Spark, and MLflow
• A strong product sense and ability to translate business objectives into technical solutions
• M.S. or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Operations Research, Economics, Mathematics)
• Excellent communication skills and a track record of cross-functional leadership

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.

I4

$137,100-$201,600 USD

I5

$167,800-$246,800 USD

I6

$203,500-$299,300 USD