Machine Learning Engineer

About The Company DoorDash is a leading technology and logistics company committed to empowering local economies by providing innovative delivery solutions. Starting with food delivery, the company has rapidly expanded its services to encompass a wide range of goods, making it a trusted platform for consumers, merchants, and delivery partners alike. With a focus on speed, reliability, and customer satisfaction, DoorDash leverages cutting-edge technology to streamline operations and enhance user experiences. The company values diversity, inclusion, and continuous growth, fostering an environment where employees can thrive and make meaningful contributions. DoorDash’s mission is to connect people with the best of their communities, and it strives to do so with integrity, empathy, and a relentless pursuit of excellence.

About The Role The Staff Machine Learning Engineer for Credit & Refund Optimization plays a pivotal role in developing intelligent, personalized systems that enhance fairness, efficiency, and trust within the DoorDash platform. This position is responsible for leading the design, development, and deployment of advanced machine learning models that optimize credit and refund decisions. These systems are crucial for balancing operational costs with long-term customer retention and satisfaction. The ideal candidate will collaborate closely with cross-functional teams—including engineering, product, and data science—to shape the strategic roadmap and ensure the successful implementation of causal inference and optimization algorithms. This role offers an exciting opportunity to influence millions of user experiences weekly, making a tangible impact on the company’s growth and customer trust.

Qualifications

• Master’s or Ph.D. degree in a quantitative field such as Computer Science, Statistics, Operations Research, Economics, or Mathematics
• Minimum of 6 years of industry experience developing machine learning systems with demonstrable business impact
• Deep expertise in statistical modeling and causal inference techniques (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 tools such as PyTorch, Spark, and MLflow
• Strong product sense with the ability to translate business objectives into technical solutions
• Excellent communication skills and a proven track record of cross-functional leadership
• Hands-on leadership experience and strong product intuition
• Willingness to engage in detailed analysis and accept constructive feedback
• Growth mindset and eagerness to expand technical and leadership skills
• Ability to adapt, demonstrate resiliency, and thrive in ambiguous, fast-changing environments

Responsibilities

• Design, develop, and deploy causal inference models to evaluate the impact of refunds and credits on customer satisfaction, retention, and behavior
• Build optimization frameworks that balance customer experience with operational costs within policy and budget constraints
• Create personalized decision systems that adapt in real-time to customer preferences and platform dynamics
• Collaborate with engineering, product, and data science teams to define and execute on the strategic roadmap for trust, service recovery, and consumer experience improvements
• Lead end-to-end model development lifecycle, including experimentation, deployment, monitoring, and iterative improvements
• Ensure models and algorithms are scalable, reliable, and aligned with business goals
• Communicate complex technical concepts effectively to non-technical stakeholders
• Stay current with industry advancements and incorporate best practices into model development

Benefits

• Competitive salary within the market range
• Opportunities for equity grants
• Comprehensive health benefits including medical, dental, and vision coverage
• 401(k) plan with employer matching
• Paid parental leave (up to 16 weeks)
• Wellness benefits and mental health programs
• Paid time off and paid sick leave in accordance with applicable laws
• Paid holidays (11 per year)
• Disability and basic life insurance
• Family-forming assistance and other employee support programs
• Flexible work arrangements, including remote options

Equal Opportunity

DoorDash is committed to fostering an inclusive and diverse workplace. We do not discriminate based on race, color, ancestry, national origin, religion, age, gender, marital or domestic partner status, sexual orientation, gender identity or expression, disability, veteran status, or any other protected characteristic. We believe that a diverse workforce enhances innovation and growth, and we actively encourage applications from individuals of all backgrounds, including women, non-binary individuals, LGBTQIA community members, people of color, differently-abled individuals, and veterans. We are dedicated to providing equal employment opportunities and ensuring a respectful, supportive environment for all employees.