Machine Learning Engineer II - Marketplace Pricing & Incentives

Machine Learning Engineer II - Marketplace Pricing & Incentives Department: Engineering Team: Machine Learning Location: San Francisco, United States Type: Full-Time **About the Role** Uber Marketplace is at the core of Uber's business, and Mobility Simulation and Planning is a critical component of Marketplace. The team's mission is to drive the growth and efficiency of the marketplace while optimizing revenue through pricing and incentives simulation and optimization. The role will provide an opportunity to work on some of the most challenging marketplace problems at Uber's scale that directly impact Uber's global business. **What You'll Do** In this role, you will develop and implement ML and optimization solutions to enhance pricing and incentive efficiency, while optimizing interactions with other marketplace components. Key responsibilities include: - Leading the design and implementation of ML-driven solutions to meet business requirements. - Managing end-to-end project execution, from scoping and offline evaluation to experimentation, production, and post-launch monitoring. - Developing and refining ML models and optimization algorithms to improve simulation accuracy and overall performance. - Collaborating with cross-functional teams, including product, operations, and science partners. **Basic Qualifications** - 2+ years of experience in an ML/optimization role, or a PhD in a relevant field (CS, OR, EE, Statistics, etc.) - Expertise in machine learning and optimization algorithms - Experience with ML frameworks - Proficiency in at least one coding language such as Python, Go, or Java - Strong communication skills and ability to work effectively with cross-functional partners - Strong sense of ownership to drive projects end-to-end **Preferred Qualifications** - Experience in translating ambiguous business problems into structured, principled technical solutions - Experience in developing and deploying optimization algorithms in production - Experience in causal inference and experimental design - Experience in evaluating ML models in a production environment For San Francisco, CA-based roles: The base salary