Nuro

Research Scientist role focused on building ML-based prediction systems for autonomous driving, involving generative sequence modeling, agent creation for simulation, and deployment on real vehicles. Requires expertise in sequential decision-making, prediction, generative modeling, and deep learning frameworks, with a preference for PhDs and publication records.

Senior ML Research Scientist focused on end-to-end autonomous driving systems, leveraging large models for perception and behavior, and deploying solutions on Nuro's autonomous vehicles. Requires expertise in ML, robotics, and experience with large-scale datasets and compute.

Nuro is seeking a Staff ML Research Scientist to solve perception, prediction, and planning problems in their self-driving system using advanced ML methods like foundation models, multi-modal LLMs, and reinforcement learning. The role involves applying and researching novel ML techniques, building ML data pipelines, and deploying autonomous software to public roads. Requires 6+ years of experience, an M.Sc. or Ph.D., and a strong publication record in relevant conferences.

Lead ML Research Scientist at Nuro, a self-driving technology company. The role focuses on solving perception, prediction, and planning problems using advanced ML methods like foundation models, multi-modal LLMs, generative models, and reinforcement learning. Responsibilities include applying and researching novel ML techniques, building ML data pipelines, providing technical leadership, and deploying autonomous software to public roads. Requires 6+ years of experience with an M.Sc. or Ph.D. in a related field, deep expertise in ML, Deep Learning, and Robotics, strong programming skills, and a publication record in major AI/ML conferences.

Research Scientist focused on developing and productizing state-of-the-art generative models (diffusion, flow matching, energy-based) for autonomous driving plan generation, leveraging foundation models and reinforcement learning for optimization and controllable generation.

Machine Learning Research Scientist focused on behavior planning and prediction for autonomous driving, using advanced ML techniques like self-supervised learning, OOD detection, RL, and generative modeling to solve real-world challenges and deploy solutions on vehicles.

Machine Learning Research Scientist focused on developing and scaling state-of-the-art generative models, particularly diffusion architectures, flow-matching, and energy-based models, for autonomous plan generation in robotics. The role involves leveraging foundation models (LLMs, world models), optimizing models with reinforcement learning and reward modeling, and developing controllable generative models. Collaboration across autonomy teams and deployment of models on NuroDriver are key aspects.