Staff Machine Learning Engineer - Mobility Verticals

Uber
Seattle, United StatesPosted 25 March 2026

Job Description

Staff Machine Learning Engineer - Mobility Verticals Department: Engineering Team: Machine Learning Location: Seattle, United States Type: Full-Time **About the Role** Uber is looking for an exceptional ML engineer to join our Mobility Marketplace Vertical team, where you'll tackle some of the most challenging problems in real-time marketplace optimization at unprecedented scale. You will develop and deploy sophisticated machine learning systems that power demand forecasting, supply/demand balancing, driver earnings prediction, and matching algorithms across our specialized mobility products: Airport, Reserve, and Rideshare. Our systems operate at massive scale, processing 1M+ predictions/second and powering billions of rides globally. The work you do will directly impact millions of riders and drivers daily, ensuring optimal marketplace efficiency whether someone is catching a flight at JFK, scheduling a ride for tomorrow morning, or sharing their commute with other passengers. You'll be working on cutting-edge problems at the intersection of machine learning, operations research, and marketplace economics—building models that need to be both highly accurate and blazingly fast, balancing multiple objectives like rider wait times, driver earnings, and overall marketplace health. This is a high-impact, high-visibility role where you'll shape the technical strategy for vertical-specific marketplace optimization, mentor talented engineers, and collaborate with world-class data scientists, product managers, and economists to push the boundaries of what's possible in mobility marketplaces. **What the Candidate Will Need / Bonus Points** - Lead technical strategy across 1+ year time horizons, setting the vision for vertical-specific marketplace optimization - Design and build end-to-end ML solutions for demand forecasting, supply balancing, and matching optimization in large-scale distributed systems - Develop sophisticated forecasting and matching approaches that combine machine learning with mathematical optimization and game theory - Collaborate closely with cross-functional teams of engineers, data scientists
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