Staff Gen AI Engineer

Staff Gen AI Engineer Department: Engineering Team: Machine Learning Location: Sunnyvale, United States Type: Full-Time **About the Role** Applied AI is a horizontal AI team at Uber partnering with product and platform teams across the company to deliver cutting-edge machine learning solutions for core business problems. The Computer Vision team in AppliedAI specializes in Generative AI, Foundation Model, and classical Computer Vision solutions, and the ML infrastructure needed to scale these systems in production. We’re looking for a Staff Engineer with deep experience in Machine Learning, Generative AI, and ML systems design to help build and scale high-impact AI solutions. In this role, you’ll lead technically complex projects, influence the architecture of ML systems, and collaborate cross-functionally to drive innovation and impact across multiple Uber surfaces. This is a great opportunity for a strong hands-on technical leader who thrives in a fast-paced, product-driven environment and wants to be at the forefront of applied AI at scale. **What the Candidate Will Do:** - Design and implement ML-driven systems that power core Uber experiences, with a focus on scalability, reliability, and performance. - Lead the technical execution of key projects involving classical ML, deep learning, and generative AI technologies (e.g., LLMs, multimodal models). - Collaborate closely with product, data science, and infrastructure teams to develop AI solutions from ideation through production deployment. - Contribute to and influence the technical direction for Applied AI, particularly around system design, model architecture, and infrastructure decisions. - Champion engineering best practices in ML development — including experimentation workflows, model versioning, evaluation, monitoring, and responsible AI. - Provide mentorship to engineers on the team and across partner orgs to help raise the technical bar. **Basic Qualifications:** - 10+ years of industry experience in machine learning and software engineering, with a proven record of delivering ML solutions to production. - Strong