ML Engineer II — Autonomous Vehicle Research & Systems

Uber; Sunnyvale (CA); On-site; USD 171,000 - 190,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Benefits

Job summary

Uber is launching an AV Labs to accelerate the autonomous technology ecosystem in Sunnyvale, CA. We are building a high-velocity team to turn real-world operations into high-quality data for autonomous partners.

The role focuses on designing frontier techniques, leading end-to-end model lifecycles, and providing technical leadership. Expect collaboration across teams and opportunities to publish research at major conferences as part of a mission-driven data race in autonomy.

Qualifications

• PhD or MS with equivalent industry experience in Computer Science, Robotics, or a related field.
• 3+ years of relevant industry experience in autonomous vehicles and/or computer vision.
• Strong understanding of connecting cutting-edge modeling techniques to AV research in a scalable, reliable way.
• Publications at leading ML and CV conferences or comparable outputs.
• Proficiency in Python and modern deep learning frameworks (PyTorch or TensorFlow).
• Strong communication skills with leadership experience across teams.

Responsibilities

• Design and develop frontier techniques for autonomous vehicle research.
• Lead end-to-end model lifecycle and system architecture from data to deployment and monitoring.
• Provide technical leadership through reviews, mentorship, and hands-on execution.
• Collaborate with engineering and product teams across AV Labs.
• Publish and present original research at top-tier CV and ML conferences.

Skills

Python

Deep learning

Model lifecycle

Mentorship

Cross-team collaboration

Education

PhD or MS in CS/Robotics or related field

Tools

PyTorch

TensorFlow

Job description

Uber is launching an AV Labs to accelerate the autonomous technology ecosystem in Sunnyvale, CA. We are building a high-velocity team to turn real-world operations into high-quality data for autonomous partners.

The role focuses on designing frontier techniques, leading end-to-end model lifecycles, and providing technical leadership. Expect collaboration across teams and opportunities to publish research at major conferences as part of a mission-driven data race in autonomy.