Sr. Staff Engineer, Matching & Segmentation

Sr. Staff Engineer, Matching & Segmentation Department: Engineering Team: Machine Learning Location: San Francisco, United States Type: Full-Time **About the Role** We are seeking a Sr. Staff Engineer and Tech Lead to join Uber's Mobility Matching & Segmentation organization. You will play a central role in architecting and evolving the ML-powered systems that determine how riders are matched with drivers in real-time and how marketplace segmentation enables differentiated products like Wait & Save, Predictive Dispatch, and XShare. You will tackle some of the most complex optimization and systems problems at Uber, working at the intersection of machine learning, distributed systems, and real-time decision-making — with your contributions directly impacting the experience of millions of users worldwide. **What the Candidate Will Do** - Be the Tech Lead for a complex domain within Matching & Segmentation, setting technical direction and driving architecture decisions across matching algorithms, segmentation models, forecasting systems, and real-time marketplace infrastructure. - Design, develop, and deploy ML and optimization systems that solve high-impact business problems at scale — including real-time matching, reinforcement learning-based dispatch, and experiment-driven product development. - Lead projects that span across orgs (e.g., matching, driver pricing, rider pricing, surge, platform) with significant cross-org dependencies and design complexity. - Collaborate closely with Scientists, Product Managers, and peer engineering teams to define technical strategy, translate business requirements into system designs, and deliver high-quality solutions. - Drive ongoing improvements in system reliability, performance, scalability, and efficiency through strong engineering practices, automation, and observability. - Mentor and grow engineers across the organization, including Senior and Staff engineers, raising the technical bar and fostering a culture of engineering excellence. - Contribute to the design and evolution of Uber's large-scale experimentation infrastructure, including Switchback experiments th