Staff Machine Learning Engineer - AV Labs

About the Role

Uber 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 race—and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match.

As a Staff 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 machine learning techniques across the autonomy systems. 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 the Candidate Will Do

Set the technical roadmap and lead the delivery of state-of-the-art Machine Learning systems:

• Strategic 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.
• End-to-End AI Innovation: Drive the adoption of end-to-end AI-driven methods for autonomy pipelines, moving beyond incremental improvements to achieve breakthrough performance.
• Architecture & System Design: Design and oversee the implementation of complex, large-scale ML systems, ensuring seamless integration between upstream sensor data.
• 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.
• Platform Evolution: Define the requirements for high-quality datasets and auto-labeling systems, ensuring our ML infrastructure evolves at the speed of the latest research.
• 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.

Basic Qualifications

• 8+ years of working experience in the ML, Robotics, or Autonomous Systems industry.
• 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).

Preferred Qualifications

• PhD degree in Computer Vision, 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.
• Recognized expertise in the field (e.g., publications in CVPR, NeurIPS, ICRA or patents related to AV).
• Experience building and scaling "Foundation Models" for physical world interaction.

For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year.

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 .

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, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form .

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.