About the job
Who We Are
Nuro is a pioneering self-driving technology company dedicated to making autonomy accessible to everyone. Established in 2016, we are developing the most scalable autonomous driving solution, merging advanced AI with high-performance automotive hardware. Our flagship technology, the Nuro Driver™, is licensed for various applications including robotaxis, commercial fleets, and personal vehicles. With years of proven self-driving deployments, Nuro provides automakers and mobility platforms with a clear trajectory towards commercial-scale AVs, fostering a safer, more connected future.
About the Role
Join our learned behavior team where we leverage sophisticated machine learning strategies to expedite software advancements. This role involves close collaboration with software teams to identify challenges and implement innovative machine learning approaches to tackle real-world problems. Your work may include self-supervised learning for robust representation, out-of-distribution detection for addressing long-tail issues, refining reinforcement learning methods for motion planning, trajectory prediction, and enhancing model robustness to address uncertainties. If you are passionate about solving complex problems with practical solutions ready for vehicle deployment, we invite you to be a part of our journey!
About the Work
- Develop scalable machine learning systems for planning and predicting safe, feasible trajectories for autonomous vehicles.
- Investigate generative sequence modeling and sequential decision-making; backgrounds in Embodied AI for robotics, Causal reasoning, Model interpretability, and Joint prediction and planning are advantageous.
- Address uncertainties arising from interconnected autonomous systems.
- Collaborate across autonomy teams to create comprehensive solutions for major autonomy challenges by understanding issues, proposing ideas, prioritizing tasks, and developing effective solutions.
- Implement practical solutions and deploy them on real-world vehicles.
About You
You possess extensive expertise and experience in one or more of the following areas:
- M. Sc. or Ph. D. in Computer Science, Artificial Intelligence, Mathematics, or a related discipline.
- Strong background in sequential decision-making, Imitation Learning, Deep Reinforcement Learning, generative modeling, and more.

