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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.
Job Responsibility:
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 that power marketplace optimization decisions
Deliver and review technical designs, code, and documentation to a high standard, and champion best practices in data management, data quality, and service deployment
Requirements:
Bachelor's degree in Computer Science, Computer Engineering, or a related technical field
8-10+ years of professional software development experience, building and operating systems in production environments
Strong knowledge of backend development, distributed systems, and system design for large-scale, low-latency applications
Experience with ML systems, optimization algorithms, or real-time decision systems in production
Demonstrated ability to lead complex, multi-team technical initiatives with significant cross-org dependencies
Excellent communication skills and the ability to collaborate effectively with cross-functional teams including Product, Science, and Operations
Proven ability to mentor and elevate other engineers, including Senior and Staff-level ICs
Nice to have:
MS or PhD in Computer Science or a related field
Deep experience with marketplace systems, matching/ranking algorithms, reinforcement learning, or forecasting systems