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NuroNuro

Senior Software Engineer, Behavior Planning

Develops state-of-the-art robotics and ML algorithms for autonomous vehicle behavior planning, enabling safe navigation in complex environments. Requires advanced robotics/ML expertise, Python/C++ proficiency, and Master's/PhD.

About the job

About the Work

  • Design and implement novel robotics and machine learning technologies for the Nuro Driver.
  • Work cross-functionally with engineers across behavior, perception, mapping, and ML research to advance the state-of-the-art in autonomous driving.
  • Implement practical solutions with production-ready software, to deploy new technologies on real vehicle platforms in a safe, performant, and scalable way.
  • Provide technical guidance and mentorship to junior members of the behavior team.

About You

  • PhD or Masters Degree in robotics, computer science, mechanical/aerospace engineering, electrical engineering, mathematics, or related field.
  • Robotics expertise in areas such as path planning, motion planning, trajectory generation, behavior planning, optimal control.
  • Machine learning experience with techniques such as deep learning, reinforcement learning, imitation learning, transformers, and diffusion models.
  • Experience in optimizing model performance through efficient processing, visualization, and analysis of large datasets.
  • Strong software development skills and Python/C++ coding proficiency.
  • Ability to collaborate within and across teams and derive best solutions from cross-functional interactions.
  • Desire to work at the edge of research and development, bringing algorithms from research into production.
  • Bonus: hands-on experience developing software for safety-critical systems, distributed training, or inference optimization.

Compensation: $193,930 - $291,150/year base pay, plus annual performance bonus, equity, and competitive benefits.

Skills

Python, C++, Path Planning, Motion Planning, Trajectory Generation, Behavior Planning, Optimal Control, Deep Learning, Reinforcement Learning, Imitation Learning

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