Machine Learning Research Scientist, Behavior Planning and Prediction

Nuro•Mountain View, CA

57d

About The Position

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!

Requirements

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)

Nice To Haves

Embodied AI for robotics
Causal reasoning
Model interpretability and explainability
Joint prediction and planning.

Responsibilities

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:
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.

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