ML Research Scientist, Prediction Smart Agents

Nuro

Mountain View, California

Full Time

Posted February 19, 2026

$194k - $291k

Not Specified

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Job Description

The role involves designing and developing advanced machine learning models to predict traffic behavior for autonomous vehicles, focusing on generative sequence modeling and simulation to improve safety and decision-making in self-driving systems.

Key Responsibilities

Design and develop scalable machine learning-based prediction systems for autonomous driving.
Build and refine models for predicting the behavior of surrounding traffic using advanced generative sequence modeling.
Collaborate with planning teams to create realistic, controllable agents for closed-loop simulation and reinforcement learning training.
Research and implement cutting-edge techniques in generative modeling, sequence prediction, and decision-making for autonomous systems.
Mitigate uncertainties across interconnected autonomy components to improve system reliability and safety.
Work with cross-functional teams to develop practical, deployable solutions for real-world autonomous vehicle applications.

Requirements

Deep expertise and prior experience in one or many of the following areas: sequential decision-making, prediction, Imitation Learning, Deep Reinforcement Learning, generative modeling, large models pretraining and finetuning, or machine learning for robotics.
Education: An M.Sc. or Ph.D. preferably focusing on Computer Science, Artificial Intelligence, Mathematics, or a closely related field.
Experience: At least 2 years of deploying machine learning systems onboard, ideally in the area of prediction.
Technical Skills: Strong problem solving and programming skills in Python required; C beneficial; experience with ML frameworks such as PyTorch.
Research and publication record: Demonstrated research publications in top conferences such as NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, ICRA, IROS, etc.
Collaboration skills: Strong culture fit and ability to work effectively as a team player.
Physical and cognitive demands: Not explicitly specified in the posting.
Other mandatory requirements: Ability to design and build scalable, machine learning-based prediction systems; conduct research in generative sequence modeling and sequential decision-making; collaborate with planning teams to develop realistic and controllable agents for closed-loop simulation; mitigate uncertainties across interconnected autonomy components; propose and develop practical, deployable solutions for real-world vehicle deployment.