ML Research Scientist, Prediction & Smart Agents

Core responsibilities:

• Design and build scalable, machine learning-based prediction systems to generate multi-modal, realistic, and kinematically feasible trajectories
• Conduct cutting-edge research in generative sequence modeling and sequential decision-making, including scalable generative sequence modeling approaches, marginal/conditional/joint distribution modeling, transformer-based architectures, large generative models, and diffusion models
• Collaborate closely with the Planning team to design realistic and controllable agents for closed-loop simulation, enabling agent training via Reinforcement Learning
• Mitigate accumulated uncertainties across interconnected autonomy components and collaborate across various autonomy teams to develop holistic solutions

This role creates positive change by developing advanced machine learning models that improve autonomous driving systems, making autonomy accessible to all and empowering a safer, richer, and more connected future through scalable self-driving technology.

Required qualifications:

• M.Sc. or Ph.D. (preferable) in Computer Science, Artificial Intelligence, Mathematics, or closely related field
• Subject matter expertise and research experience in sequential decision-making, prediction, Imitation Learning, Deep Reinforcement Learning, generative modeling, large models, or machine learning for robotics
• Strong problem solving and programming skills in Python (required) and C++ (beneficial) with ML frameworks such as PyTorch
• 2+ years of experience deploying machine learning systems onboard, ideally in prediction
• Demonstrated research publications in top conferences (NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, ICRA, IROS, etc.)

Compensation and benefits:

• Base pay range: $193,930 - $291,150 annually
• Annual performance bonus
• Equity
• Competitive benefits package
• Commitment to diversity, inclusion, and psychological safety for all employees

Nuro is a self-driving technology company on a mission to make autonomy accessible to all, building the world's most scalable driver by combining cutting-edge AI with automotive-grade hardware and licensing its core technology to support applications from robotaxis to personally owned vehicles.