Software Engineer, Machine Learning - Credit & Refund OptimizationFairygodboss • San Francisco, California, United States

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Software Engineer, Machine Learning - Credit & Refund Optimization

Fairygodboss

San Francisco, California, United States

San Francisco, California, United States

Jetzt Bewerben

Über

About the Team Join the team focused on building intelligent, personalized systems that drive fairness, efficiency, and trust on the DoorDash platform. We own the credits and refunds experience, key components of customer satisfaction and retention, and we pioneer ways to optimize and personalize these decisions at scale using causal inference and optimization. About the Role Machine Learning Engineer Lead the development of state‑of‑the‑art ML systems that personalize and optimize credits and refund decisions, balancing cost efficiency with long‑term customer retention and experience. Responsibilities Design and deploy causal inference models to assess the impact of refunds and credits on customer satisfaction, retention, and behavior. Develop optimization frameworks that balance customer experience with operational cost, under policy and budget constraints. Build personalized decision systems that adapt to customer preferences and platform dynamics in real time. Collaborate with engineering, product, and data science partners to shape the roadmap for trust, service recovery, and consumer experience. Lead end‑to‑end model development, including experimentation, deployment, monitoring, and iteration. Qualifications 3+ years of industry experience delivering machine learning systems with clear business impact, especially in personalization, optimization, or causal inference. Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) throughout the software development lifecycle. Deep expertise in statistical modeling and causal inference (uplift modeling, treatment effect estimation, synthetic controls, instrumental variables). Experience designing and deploying optimization algorithms such as 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. MS or PhD in a quantitative field (Computer Science, Statistics, Operations Research, Economics, Mathematics). Excellent communication skills and a track record of cross‑functional leadership. Compensation Base salary range for the role in the United States (including Illinois and Colorado) is $137,100–$299,300 USD depending on level, with opportunities for equity grants. Benefits Comprehensive benefits package: 401(k) plan with employer matching, paid parental leave, wellness benefits, commuter benefits, paid time off and sick leave, medical, dental, and vision coverage, 11 paid holidays, disability and life insurance, family‑forming assistance, and a mental health program. EEO Statement Statement of Non‑Discrimination: no employee or applicant will face discrimination or harassment based on race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. We encourage applicants of all backgrounds, including women, non‑binary or gender non‑conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently‑abled, caretakers and parents, and veterans.
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San Francisco, California, United States

Sprachkenntnisse

English

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