NVIDIA is searching for a senior or principal engineer who specializes in large-scale reinforcement learning and policy learning in the Generalist Embodied Agent Research (GEAR) group. Our team is leading Project GR00T, NVIDIA’s moonshot initiative at building foundation models and full-stack technology for humanoid robots. 

You will work with an amazing and collaborative research team that consistently produces influential works on multimodal foundation models, large-scale robot learning, embodied AI, and physics simulation. Our past projects include Eureka, VIMA, Voyager, MineDojo, MimicPlay, Prismer, and more. Your contributions will have a significant impact on our research projects and product roadmaps.

What you will be doing:

 Develop a large-scale reinforcement learning training framework capable of running on thousands of GPUs; 

Build and optimize simulation infrastructure (based on GPU-accelerated simulators like Isaac Lab) to support the training of locomotion and manipulation policies for robots at scale;

Develop sim-to-real transfer pipelines and work closely with the robotics team to deploy to physical robots;

Propose scalable solutions that combine LLMs with policy learning. Example work: Eureka;

Apply reinforcement learning to finetune multimodal LLMs. 

What we need to see:

Bachelor’s degree or above in Computer Science, Robotics, Engineering, or a related field;

5+ years of industry experience on large-scale deep learning or MLOps;

Exceptional engineering skills in building, testing, and maintaining scalable distributed GPU training frameworks;

Proficiency in Python. Hands-on model training experience in PyTorch, JAX, or Tensorflow;

Deep familiarity with reinforcement learning algorithms like PPO, SAC, or Q-learning, including experience tuning hyperparameters and reward functions;

Familiarity with common policy learning techniques like reward shaping, domain randomization, curriculum learning;

Strong experience with large-scale GPU clusters, HPC environments, and job scheduling/orchestration tools (e.g., SLURM, Kubernetes).

Ways to stand out from the crowd:

Master’s or PhD’s degree in Computer Science, Robotics, Engineering, or a related field;

Demonstrated experience transferring policies from simulation to real robots for locomotion and manipulation;

Contributions to popular open-source reinforcement learning frameworks or research publications in top-tier AI conferences, such as NeurIPS, ICRA, ICLR, CoRL;

Strong ability to mentor junior engineers or researchers and lead technical projects from conception to completion.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world. Please join us and be part of the forefront of developing general-purpose robots and large-scale foundation models! 

The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.