Staff Machine Learning Engineer - Delivery Courier Pricing

Staff Machine Learning Engineer - Delivery Courier Pricing Department: Engineering Team: Machine Learning Location: San Francisco, United States Type: Full-Time **About the Role** The Courier Pricing team sits within Uber's Delivery Marketplace org and plays a key role in shaping pricing across food, grocery, and other delivery verticals. We work closely with cross-functional teams to develop scalable pricing products that keep our marketplace efficient, reliable, and ready to grow. As a Staff Machine Learning Engineer, you’ll build a world-class pricing system that efficiently prices every offer made to Uber’s delivery partners—impacting hundreds of millions of consumers and millions of merchants worldwide. **What You Will Do** ##### **Technical Leadership & Innovation** - Lead the design and implementation of advanced ML systems for courier pricing algorithms serving millions of couriers - Own end-to-end ML model lifecycle from research through production deployment and continuous optimization ##### **Platform & Architecture** - Build scalable ML architecture and feature management systems supporting Courier Pricing and broader Marketplace teams - Design experimentation frameworks enabling rapid testing of pricing algorithms using A/B, Switchback, Synthetic Control, and other experimental methodologies - Establish ML engineering best practices, monitoring, and operational excellence across the organization - Create platform abstractions that enable other ML engineers to iterate faster on pricing algorithms ##### **Cross-Functional Impact** - Collaborate with Marketplace Engineering and Science teams to productionize cutting-edge ML research - Work with Platform Engineering teams to ensure ML systems meet reliability and performance standards - Influence technical roadmaps across multiple teams through technical leadership and strategic thinking ##### **Team Development** - Mentor and grow senior ML engineers, establishing technical standards and engineering culture - Lead technical discussions and architecture reviews for complex ML systems **Basic Qualifications** - Bachelors (or higher) in Computer Science,