Staff Machine Learning Engineer - Av Labs

Uber Uber · Consumer · Sunnyvale, CA · Engineering

Staff ML Engineer at Uber's AV Labs focused on Physical AI, developing advanced autonomy algorithms and models to add semantics to driving data. The role involves leading the technical roadmap for ML systems, designing large-scale ML systems, mentoring engineers, and evolving ML infrastructure for autonomous driving.

What you'd actually do

  1. Lead the strategy for development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake.
  2. Design and oversee the implementation of complex, large-scale ML systems, ensuring seamless integration between upstream sensor data.
  3. Mentor senior and lead engineers, fostering a culture of rigorous experimentation and engineering excellence. You will influence the technical direction of multiple teams.
  4. Define the requirements for high-quality datasets and auto-labeling systems, ensuring our ML infrastructure evolves at the speed of the latest research.
  5. Act as a bridge between AV Labs and other Uber engineering units to ensure that autonomous technology is successfully integrated and deployed at scale.

Skills

Required

  • Python
  • Linux
  • PyTorch
  • ML frameworks
  • large-scale technical projects
  • Robotics
  • Autonomous Systems

Nice to have

  • C++
  • CUDA
  • high-performance system optimization
  • Robot Operating System (ROS)
  • autonomous middleware
  • publications in CVPR, NeurIPS, ICRA
  • patents related to AV
  • Foundation Models for physical world interaction

What the JD emphasized

  • unlocking real-world, long-tail driving data
  • Physical AI
  • advanced autonomy algorithms and models
  • rich semantics
  • complex urban edge cases
  • foundation models
  • autonomous technology

Other signals

  • autonomous driving
  • foundation models
  • data mining
  • scene understanding
  • causal modeling