Engineering Manager II, Computer Vision - Applied AI

Engineering Manager II, Computer Vision - Applied AI Department: Engineering Team: Machine Learning Location: Seattle, United States Type: Full-Time **About the Role** Applied AI at Uber builds intelligent systems that power critical product experiences across the platform. As an Engineering Manager II — Computer Vision, you will lead a high-performing team of engineers developing state-of-the-art vision and multimodal systems that support large-scale, production-grade applications such as document intelligence, onboarding automation, transcription systems, and other visual AI workflows. You will be responsible for driving technical execution and long-term strategy across computer vision initiatives, partnering closely with Product, ML Infrastructure, and cross-functional stakeholders. This role requires strong technical depth in machine learning systems and distributed production environments, combined with exceptional people leadership and organizational impact. You will shape multi-year technical direction, elevate engineering standards, and ensure your team delivers reliable, scalable, and high-quality AI solutions that drive measurable business impact. **What You Will Do:** - Lead and manage a team of software and deep learning engineers, delivering high-quality computer vision products and scalable ML systems. - Develop and execute technical strategies that align with business objectives, translating complex product requirements into clear, multi-quarter roadmaps and platform architecture. - Collaborate cross-functionally with Product, ML Infra, Data, and partner engineering teams to drive technical innovation and deliver measurable impact across business units. - Plan, prioritize, and oversee execution, ensuring timely delivery through effective delegation, empowering tech leads, and maintaining high engineering standards. - Mentor, grow, and develop a world-class team of deep learning engineers, fostering a culture of continuous learning, operational excellence, and high performance. **Basic Qualifications:** - Bachelor’s degree in Computer Science, Engineering, or equivalent technical background