3 days ago
Base Salary
$184k - $357k/yr
Responsibilities
- Build simulation frameworks for training and evaluating robot foundation models on NVIDIA Omniverse.
- Design, implement, and evaluate novel robot-learning algorithms with research teams.
- Drive technical architecture, evaluation standards, and cross-team leadership between Research and Product.
- Develop production-ready Isaac Lab Arena capabilities from research prototypes and user feedback.
- Train and evaluate robot foundation models and integrate LLM and agentic workflows into robotics simulations.
- Participate in software design and code reviews, testing, continuous integration, and deployment.
- Collaborate with researchers and product engineers and stay current with robotics research.
Requirements
- PhD 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.
- Ability to translate research prototypes into production-ready software platforms.
- Proven software design experience.
- Proficiency with Python and deep learning software stacks such as PyTorch and JAX.
- Preferred: high-impact publications at robotics and machine-learning venues such as CoRL, RSS, ICRA, or NeurIPS.
- Preferred: reinforcement learning or imitation learning expertise.
- Preferred: expertise in GPU-accelerated physics simulation engines such as PhysX, Isaac Gym, Isaac Lab, or Newton.
- Preferred: experience with CUDA, Warp, Isaac Lab, or ROS and with maintaining open-source projects.
Benefits
- Eligible for equity and benefits.
- Base salary varies by location, experience, and comparable employee pay; the listed ranges are $184,000-$287,500 for Level 4 and $224,000-$356,500 for Level 5.
- Applications are accepted at least until October 31, 2026.
Categories
ML EngineeringRobotics
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.