Staff ML Research Scientist

Nuro Nuro · Robotics · CA · Autonomy

Nuro is seeking a Staff ML Research Scientist to solve perception, prediction, and planning problems in their self-driving system using advanced ML methods like foundation models, multi-modal LLMs, and reinforcement learning. The role involves applying and researching novel ML techniques, building ML data pipelines, and deploying autonomous software to public roads. Requires 6+ years of experience, an M.Sc. or Ph.D., and a strong publication record in relevant conferences.

What you'd actually do

  1. Apply and research novel and advanced machine-learning techniques
  2. Solve perception, prediction, and planning problems in a state-of-the-art autonomy system
  3. Build and leverage effective and efficient ML data pipelines
  4. Provide technical and people leadership to a large team
  5. Production and deploy autonomous software to public roads

Skills

Required

  • 6+ years of work experience with an M.Sc. or Ph.D.
  • Deep subject matter expertise and research in Machine Learning, Deep Learning, Robotics
  • Strong problem solving and programming skills in C++ or Python
  • Demonstrated research publications in any of the major conferences (RSS, ICRA, CoRL, CVPR, ICLR, ICML, NeurIPS, ICCV, AAAI, etc.)

Nice to have

  • expertise in foundation models
  • multi-modal LLMs
  • generative models
  • out-of-distribution detection
  • imitation learning
  • reinforcement learning

What the JD emphasized

  • novel and advanced machine learning methods
  • foundation models
  • multi-modal LLMs
  • generative models
  • out-of-distribution detection
  • imitation learning
  • reinforcement learning
  • Demonstrated research publications in any of the major conferences (RSS, ICRA, CoRL, CVPR, ICLR, ICML, NeurIPS, ICCV, AAAI, etc.)

Other signals

  • novel and advanced machine learning methods
  • foundation models
  • multi-modal LLMs
  • generative models
  • out-of-distribution detection
  • imitation learning
  • reinforcement learning
  • perception, prediction, and planning problems
  • deploying those solutions into the real world
  • ML data pipelines
  • autonomous software to public roads