Principal Machine Learning Engineer AutonomyMachine Learning, Engineering San Francisco, California | Sunnyvale, California Full Time

About the RoleAs a Principal ML Engineer, you will be at the forefront of Physical AI, developing core components of our Autonomous Driving stack.

You will set the technical direction for the development and implementation of state-of-the-art machine learning across the autonomy pipeline. You aren't just solving known problems; you are identifying the next generation of challenges in AV, designing the architectural foundations to solve them, and raising the bar for technical excellence across the entire engineering organization.

You will collaborate with engineers across big data, compute, and cloud engineering to build platforms that harness scale and real-world complexity to reimagine how the world moves.

What You'll DoStrategic Autonomy Development: Lead the strategy for Autonomous Driving Algorithm Development, ensuring our stack is robust, safe, and capable of handling the most complex urban edge cases

Next-Generation Autonomy: Provide the overarching technical vision for our multi-modal autonomy systems.

You will lead the design of state-of-the-art foundation models to achieve highly accurate, real-time understanding of the world, and seamlessly translate this semantic understanding into cutting-edge Physical AI models that dictate safe, human-like decision-making and trajectory generation

Architecture & System Design: Design and oversee the implementation of complex, large-scale ML systems, ensuring seamless integration between upstream sensor data and downstream actuation, while relentlessly optimizing deep learning models for strict onboard latency, compute, and kinematic constraints

Technical Mentorship & Influence: Mentor senior and lead engineers, fostering a culture of rigorous experimentation and engineering excellence.

You will influence the technical direction of multiple teams

Cross-Organizational Leadership: Act as a bridge between AV Labs and other Uber engineering units to ensure that autonomous technology is successfully integrated and deployed at scale

What You'll Need10

• years of working experience in the ML, Robotics, or Autonomous Systems industry (building upon the base 8

• years expected for advanced roles)

Proven experience leading large-scale technical projects from conception to production

Bachelor's degree in Computer Science, Computer Engineering, or related fields

Expert-level proficiency in Python and Linux environments

Deep expertise in modern AI/ML frameworks (e.g., PyTorch)

Bonus Points IfPhD degree in Robotics or Machine Learning with a focus on Autonomous Driving

Extensive experience with C

•

• , CUDA, and high-performance system optimization

Deep understanding of the Robot Operating System (ROS) or similar autonomous middleware

Experience building and scaling "Foundation Models" for physical world interaction

Recognized expertise in the field (e.g., relevant patents, open-source contributions, or publications)

About the TeamUber is launching AV Labs to accelerate the autonomous technology ecosystem. We're building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team is focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data raceand Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match.