Staff/Lead Machine Learning Engineer (Behavior & Planning)

• We are looking for a Staff Machine Learning Engineer to be a technical leader on Nuro’s Behavior & Planning team
• Our team owns how the Nuro Driver behaves on the road: prediction, decision making, and planning, and is responsible for turning Nuro’s large-scale driving data into safe, comfortable, and natural driving behavior
• In this role you will bring strong, general machine learning expertise to some of the hardest problems in autonomy and drive them from research through to deployment on real vehicles
• You’ll work at the frontier of applied ML spanning areas such as foundation and world models, LLM/VLM reasoning, reinforcement and imitation learning, generative and diffusion models, and transformer-based prediction and planning
• You’ll apply this knowledge and experience to make our driving generalize as we scale across new geographies as we expand throughout the U.S. and globally, and across new vehicle platforms including robotaxi, personally owned vehicles, and delivery/logistics
• This is a high-ownership role
• You will set technical direction, lead initiatives that span multiple teams, and operate with a high degree of autonomy and minimal oversight
• For the right person, it offers a clear path to grow into a management or tech-lead role as the team scales
• If you love solving hard new problems and seeing your models drive real robots in the physical world, come join us!
• Technical Leadership: Lead ML initiatives across the autonomy stack framing ambiguous problems, setting technical direction, and driving them from idea to on-road deployment with minimal oversight
• Applied ML at the Frontier: Design, train, and productionize state-of-the-art models across some or many of: foundation and world models, LLM/VLM reasoning, reinforcement and imitation learning, generative and diffusion models, and transformer-based prediction and planning
• Generalization & Scale: Build behavior and planning models that generalize to new cities and geographies (U.S. and global) and adapt to new vehicle platforms
• Cross-Functional Collaboration: Partner closely with Perception, Simulation & Evaluation, and ML Infra & Data, as well as the broader Autonomy and Research orgs, to develop holistic solutions to top autonomy challenges, align on priorities, and unblock shared initiatives
• End-to-End Ownership: Own the full model lifecycle: data, training, onboard inference, closed-loop and open-loop evaluation, and continuous on-road iteration
• Mentorship & Influence: Raise the technical bar of the team, mentor engineers and researchers, and shape roadmap and technical strategy beyond your immediate scope

Benefits

• Free Caltrain pass and commuter benefits
• Company stock options
• Work from home opportunities
• Health insurance- M.S. or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or a related field or equivalent practical experience
• Demonstrated ability to lead initiatives, collaborate across many different teams, and operate independently with minimal oversight
• Strong, general machine learning foundations. You can reason from first principles across model architectures, training, and evaluation, and clearly explain and apply state-of-the-art techniques. Depth in some of: sequential decision making, prediction, generative modeling, foundation/world models, or representation learning
• 7+ years building and deploying machine learning systems, with a track record of leading complex, multi-team technical initiatives
• Efficient and clear communication skills are a must, with the ability to align cross-functional stakeholders
• Strong problem-solving and programming skills in Python (required) and/or C++
• Understanding of the full ML development cycle, from data collection and training to deployment, onboard inference considerations, and data iteration loops
• Strong preference for prior experience in autonomous vehicles or robotics, and familiarity with how ML fits into a complete autonomy/planning stack, though we hire strong general-ML talent from adjacent domains and value the ability to ramp on a new domain quickly
• Experience mentoring engineers or leading a team, and interest in growing into a management or tech-lead track
• Familiarity with at least one major ML framework (PyTorch, JAX, TensorFlow)
• Research contributions in top venues (e.g., NeurIPS, ICLR, ICML, CVPR, RSS, CoRL) are a plus, but a strong track record of applied and production impact matters more