Software Engineering Intern, Robot Learning Platform - Fall 2026

NVIDIA • Santa Clara, CA

1d

About The Position

NVIDIA is leveraging AI to advance computing, with GPUs powering AI in computers, robots, and self-driving cars. The company fosters a diverse and encouraging work environment. This role is for a Software Engineering Intern to join the Isaac Lab team, NVIDIA's flagship platform for robotic learning. Isaac Lab supports large-scale parallelized reinforcement learning, teleoperation, and imitation learning, and is an open-source project used by top research labs and industry for training robots. The team's mission is to establish Isaac Lab as the industry's leading tool for training autonomous systems and shaping the future of robotics and AI.

Requirements

• Pursuing MS or PhD degree in Computer Science, Mechanical Engineering, Robotics, or similar program area
• Experience in software development with Python and the deep-learning software stack (Pytorch, Tensorflow, Jax, etc.)
• Experience with robotics and simulation workflows, including reinforcement learning and imitation learning in simulators such as Isaac Lab, Isaac Gym, MuJoCo, or other physics-based simulators

Nice To Haves

• Experience training a robot in simulation and deployed the policy sim-to-real
• Publications in major AI and robotics conferences

Responsibilities

• Develop the next features for our platform, such as integration with Newton simulation, scalable perception-in-the-loop reinforcement learning and learning from demonstration via tele-operation
• Participate in open-source development of Isaac Lab, including engaging with the robotics industrial and research communities
• Scale training massively in the cloud, while ensuring the highest performance with extensive benchmarking, profiling, and optimizations
• Build and improve the robot asset pipeline, importing URDF/MJCF models, authoring new environments, and validating physical fidelity against real-world hardware
• Bridge the sim-to-real gap by working on domain randomization, system identification, and transfer techniques that move policies from simulation onto physical robots

Benefits

• Intern benefits

What This Job Offers

• Career Level: Intern
• Education Level: Ph.D. or professional degree