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Principal Machine Learning Engineer – Autonomy

United States, San Francisco Employment contract 302000.00 - 336000.00 USD / Year · Job Posted May 04, 2026
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Job Description

As 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.

Job Responsibility

  • Lead the strategy for Autonomous Driving Algorithm Development, ensuring our stack is robust, safe, and capable of handling the most complex urban edge cases
  • Provide the overarching technical vision for our multi-modal autonomy systems
  • Design and oversee the implementation of complex, large-scale ML systems
  • Mentor senior and lead engineers
  • Act as a bridge between AV Labs and other Uber engineering units

Requirements

  • 10+ 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)

Nice to have

  • PhD 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)

What we offer

  • Bonus program
  • Equity award
  • Other types of compensation
  • 401(k) plan

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