Machine Learning Research Scientist: Generative Modeling for Planning

What you'll do

• Develop and scale generative models for autonomous plan generation, including diffusion, flow-matching, and energy-based approaches.
• Optimize and control generative models using reinforcement learning, rewards, and learned verifiers; explore joint prediction and planning, self-play, active learning, and world modeling.
• Collaborate across autonomy teams and evaluate solutions by deploying models on the NuroDriver.

What they ask for

• Research experience in generative models, particularly diffusion models, flow matching, or energy-based models, for robotics, path planning, or autonomous driving.
• Strong problem-solving and programming skills in Python and/or C++.
• Demonstrated research publications in top conferences.

Nice to have

• Ph.D. (preferred); alternatively, an M.Sc. with 2–3 years of experience working with generative models.
• Experience with vision-language-action models, reinforcement learning for generative model optimization, video or text-to-image generation, diffusion models for LLMs, or world foundation models.

Pay

$160,360 and $240,540/ year (USD, base pay)

Tools

diffusion models, flow matching, energy-based models, Python, C++, reinforcement learning, large language models, world foundation models

AI focus

Generative modeling for autonomous planning, reasoning, decision-making, multimodal generation, and world modeling.