Graduate PhD Software Engineer II (Mobility Matching), United States

Graduate PhD Software Engineer II (Mobility Matching), United States Department: University Team: Engineering Location: Seattle, United States Type: Direct UTA Full-Time Working at Uber as a Graduate PhD Software Engineer II means taking deep technical expertise in AI, machine learning, and optimization and applying it to high-stakes, real-world systems. This is not a theoretical exercise; you will be building and deploying production-grade ML and algorithmic systems that operate at massive scale, where latency, reliability, and performance directly shape the experience of millions of riders and drivers. You’ll join the Mobility Matching team, a core part of Uber’s Marketplace (PIMS) organization, which develops and optimizes the algorithms that match supply (drivers) with demand (riders) in real time. Our team tackles complex large-scale allocation and decision-making problems—leveraging machine learning, reinforcement learning, and optimization to improve marketplace efficiency, reliability, and long-term ecosystem health. Improvements in these systems drive hundreds of millions of dollars in impact while reducing wasted time for users around the world. The pace here is fast, and the systems are complex and deeply interconnected. We are looking for researchers who want to be practitioners—individuals who can translate state-of-the-art research into scalable production systems. If you are energized by bridging cutting-edge ML with real-world deployment and want to own outcomes end-to-end in a high-impact environment, this is where you’ll grow. ### **What you’ll do** - Design, build, and deploy production-grade machine learning and optimization systems that power Uber’s real-time driver–rider matching - Develop and apply advanced techniques such as reinforcement learning, large-scale optimization, causal inference, and online experimentation to improve marketplace efficiency - Translate academic research and state-of-the-art ML advancements into scalable, high-impact marketplace solutions - Architect and enhance machine learning and serving infrastructure to support high-throughput training, low-latency inference, and real-time