Machine Learning Research Scientist, Behavior Planning and Prediction

Who We Are

Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world's most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale-empowering a safer, richer, and more connected future.
About the Role

The mandate of the learned behavior team is to use advanced machine learning techniques to accelerate software progress. In this role, you will work closely with the software vertical teams to understand their pain points and explore novel and advanced machine learning methods to solve practical real-world challenging problems. To name a few, using self-supervised learning to learn robust representations, exploring techniques for out-of-distribution detection to solve long tail problems, adjusting reinforcement learning techniques for motion planning, working on trajectory prediction and motion planning, investigating the robustness of models to mitigate uncertainties, or trying to build an end-to-end driving system. If you love solving challenging new problems with a mindset of deriving practical solutions to eventually be used on the vehicle, come join us!
About the Work

• Work on scalable machine learning based planning and prediction systems to generate safe and feasible trajectories for autonomous driving.
• Research generative sequence modeling and sequential decision making. Research backgrounds we are looking for but not limited to are:
• Nice to have: Embodied AI for robotics, Causal reasoning, Model interpretability and explainability, Joint prediction and planning.
• Mitigate uncertainties accumulated through interconnected autonomy components.
• Collaborate across autonomy teams while developing holistic solutions to top autonomy challenges. Understand issues, propose ideas, prioritize work and develop solutions to solve them.
• Derive practical solutions and deploy them on real-world vehicles.

About You

You have deep expertise and prior experience in some or many of the following areas:

• You have an M.Sc. or Ph.D. (preferable) focusing on one or more of the following areas: Computer Science, Artificial Intelligence, Mathematics, or a closely related field
• You have subject matter expertise and research in one or more of the following areas: sequential decision making, Imitation Learning, Deep Reinforcement Learning, generative modeling, large models (pretraining/finetuning), machine learning for robotics.
• You have strong problem solving and programming skills in Python (required) and C++ (beneficial)
• Strong culture fit and good team player
• Demonstrated research publications in top conferences (e.g. NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, ICRA)

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $160,360 and $240,540/ year for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.