Staff Machine Learning Engineer

Staff Machine Learning Engineer Department: Engineering Team: Machine Learning Location: San Francisco, United States Type: Full-Time The **Marketplace Signals** team at Uber is responsible for building and optimizing foundational marketplace signals that power user experiences and drive marketplace efficiency. Our team ensures that key signals—such as eyeball ETA, spinner time, and supply reliability indicators—are leveraged effectively across various Uber products and levers, enabling data-driven decision-making and seamless coordination across different business functions. **What You'll Do** - Develop and optimize ML models to enhance key marketplace signals (e.g., ETA predictions, supply availability metrics, demand forecasts). - Collaborate with cross-functional teams (Pricing, Matching, Driver Incentives, etc.) to ensure marketplace signals are effectively utilized. - Improve operational efficiency by building a centralized, scalable system for marketplace signals that serves multiple use cases. - Leverage cutting-edge ML techniques (deep learning, probabilistic modeling, reinforcement learning, etc.) to continuously refine marketplace signals. **What You'll Need** - Strong problem-solving skills, with expertise in ML methodologies - Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems) - Experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java **Why Join Us?** - Work on high-impact machine learning problems that directly improve Uber's marketplace efficiency. - Influence key business levers that optimize Uber’s pricing, matching, and rider/driver experience. - Build centralized marketplace signals that reduce redundancy and improve operational efficiency. - Join a high-caliber, innovative team tackling some of the hardest ML challenges in the industry. If you’re passionate about using ML to optimize real-world systems at a massive scale, we’d love to hear from you! **What You Will Do:** - Devel