Description
In the NVIDIA Isaac team, we build tools that bring the power of the GPU to bear on one of today’s grand challenges: physical AI. We’re looking for a research engineer to join our team to develop simulation tools built for scientists and companies that are using machine learning to solve the future of robotics.
You will drive cross-team collaboration between Isaac product engineering and NVIDIA Robotics research: translating research ideas into product-ready Isaac Lab Arena capabilities, bringing product and user feedback back into the research loop, and driving adoption with research users. You'll join a team of robotics engineers who work at the intersection of simulation and machine learning. Our goal is to build the industry's leading tool for evaluating robot foundation models in simulation.
Responsibilities:
- Building simulation frameworks for training and evaluating robot foundation models on top of NVIDIA's Omniverse platform.
- Partner directly with research to design, implement, and evaluate novel algorithms for robot learning.
- Driving technical architecture, setting evaluation standards, and cross-team leadership between Research and Product.
- Working as part of a high-paced software engineering team: design/code reviews, testing, continuous integration, deployment.
- Training and evaluating robot foundation models.
- Integrating modern LLM and agentic workflows into simulation and robotics workflows.
- Working with researchers and product engineers to translate research ideas into Isaac Lab Arena capabilities that can scale to NVIDIA's user base.
- Keeping up to date with the state-of-the-art in robotics research.
Requirements:
- PhD degree in Computer Science, Robotics, or a related field (or equivalent experience).
- 8+ years of relevant industry or post-degree research engineering experience in robotics, simulation, or robot learning, with ability to translate research prototypes into product or platform capabilities.
- Proven track record of software design and translating research prototypes into production-ready software platforms.
- Proficiency using Python and development experience with deep learning software stacks (Pytorch, Jax, etc.).
Preferred Qualifications:
- High-impact publications at top robotics and machine learning venues (e.g., CoRL, RSS, ICRA, NeurIPS).
- Robot learning expertise with reinforcement learning and/or imitation learning,
- Deep expertise in GPU-accelerated physics simulation engines (e.g., PhysX, Isaac Gym/Isaac Lab, Newton).
- Experience with NVIDIA robotics ecosystem tools (CUDA, warp, Isaac Lab, ROS).
- Developing and maintaining open-source projects.
You will also be eligible for equity and benefits.