Software Engineer, Machine Learning - Credit & Refund Optimization
About The Position
Join the team focused on building intelligent, personalized systems that drive fairness, efficiency, and trust in the DoorDash platform. We own the credits and refunds experience—key components of customer satisfaction and retention—and we’re pioneering new ways to optimize and personalize these decisions at scale using causal inference and optimization. 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.
Requirements
- 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
Responsibilities
- 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
Benefits
- 401(k) plan with employer matching
- 16 weeks of paid parental leave
- wellness benefits
- commuter benefits match
- paid time off
- paid sick leave
- medical benefits
- dental benefits
- vision benefits
- 11 paid holidays
- disability and basic life insurance
- family-forming assistance
- mental health program
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What This Job Offers
Job Type
Full-time
Career Level
Senior
