Senior ML Engineer, Computer Vision - Applied AI

Senior ML Engineer, Computer Vision - Applied AI Department: Engineering Team: Machine Learning Location: San Francisco, United States Type: Full-Time **About the Role** Applied AI at Uber builds intelligent systems that power critical product experiences across the platform. As a Senior Machine Learning Engineer — Computer Vision, you will develop and deploy state-of-the-art vision and multimodal models that enable scalable document understanding and transcription systems across Uber’s ecosystem. Your work will power high-impact applications such as earner onboarding verification, receipt transcription, restaurant menu digitization, and other document intelligence workflows. You will design, train, and optimize modern computer vision and vision-language models, integrating them into production systems that operate reliably at large scale. This role combines deep model development expertise with production engineering rigor — ideal for someone who thrives at the intersection of research innovation and real-world deployment. For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link [https://jobs.uber.com/en/benefits](https://jobs.uber.com/en/benefits). Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age