Software Engineer II - Machine Learning, Marketplace/Maps/Membership/AV

Software Engineer II - Machine Learning, Marketplace/Maps/Membership/AV Department: Engineering Team: Machine Learning Location: San Francisco, United States Type: Full-Time **About the Role** Collaborates with stakeholders to design, develop, optimize, and productionize machine learning (ML) or ML-based solutions and systems that are used within a team to solve moderately complex problems. **About the Team****(We are hiring for multiple teams)** We are building the future of Uber's mobility and logistics platforms. As a software engineer, you will contribute to high-scale, strategically critical systems that impact millions of users and redefine the global transportation and membership landscape.Our teams drive innovation across critical areas including: - **Maps & Routing:** Building the core technologies for location accuracy, sensor data processing, and state-of-the-art routing algorithms to power ETAs, navigation, and matching for all Uber products. - **Uber One Membership:** Enhancing user experience and growth for Uber One, a fast-growing program providing members with exclusive benefits, best prices, and priority across the platform. - **Delivery Marketplace:** Delivery Marketplace is a central pillar of Uber’s delivery products, serving as the "brain" of the operation. We drive every decision that enables orders to go from point A to point B — from Uber Eats & Grocery, to newer verticals like Uber Direct and Connect. We’re responsible for everything: from dispatch decisions, predicting food ready time, delivery times, and optimizing pickup times, to ensuring we deliver the most efficient and impactful solutions for Uber’s most critical business goals - **Autonomous Mobility & Delivery (AM&D):** Pioneering the integration of autonomous vehicles into the existing ecosystem, tackling the complex challenge of building a reliable, efficient, and scalable hybrid marketplace for both Rides and Eats. **What You’ll Do** - Design, build, and deploy scalable machine learning models to production to solve real-world business problems. - Collaborate with cross-engineering teams, data scientists and other partners to gather requirement