Senior Research Engineer for Reinforcement Learning

NVIDIA is seeking a senior or principal engineer specializing in large-scale reinforcement learning and policy learning for their Generalist Embodied Agent Research (GEAR) group. This role is part of Project GR00T, NVIDIA's ambitious initiative to develop foundation models and technology for humanoid robots. The position offers the opportunity to work with a distinguished research team known for influential work in multimodal foundation models, robot learning, embodied AI, and physics simulation.

The role combines cutting-edge research with practical engineering challenges, requiring expertise in both reinforcement learning and large-scale distributed systems. Key responsibilities include developing training frameworks that can scale to thousands of GPUs, building simulation infrastructure for robot training, and implementing sim-to-real transfer solutions. The successful candidate will work directly with the robotics team to deploy solutions on physical robots and contribute to innovative projects combining LLMs with policy learning.

This position at NVIDIA, a global leader in accelerated computing, offers competitive compensation including a base salary range of $148,000-$287,500 USD, plus equity and benefits. The company's work in AI and digital twins is transforming major industries, making this an opportunity to contribute to groundbreaking technological advances. The role is based in Santa Clara, CA, and requires 5+ years of industry experience, strong engineering skills, and deep expertise in reinforcement learning.

The ideal candidate will have advanced degrees in relevant fields, experience with robot policy transfer, and a track record of contributions to open-source frameworks or research publications. This position offers the chance to be at the forefront of developing general-purpose robots and large-scale foundation models while working with some of the most innovative minds in the industry.