Nvidia Senior Research Engineer Reinforcement Learning 

United States, California 

315274549

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

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:;

• 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 jobscheduling/orchestrationtools (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.