About the job
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.
Responsibilities
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.
Qualifications
Minimum
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.
Preferred
MS or PhD in Computer Science or a related field.
Deep experience with marketplace systems, matching/ranking algorithms, reinforcement learning, or forecasting systems.
Experience designing and running large-scale online experiments (e.g., Switchback, A/B testing frameworks).
Proficiency in languages such as Go, Java, or Python, with strong foundations in performance optimization and debugging across complex stacks.
Strong analytical and problem-solving skills with comfort navigating ambiguous, high-impact problem spaces.
Track record of driving both technical innovation and raising organizational engineering standards.