Robotics Research Engineer - Robot Simulation and Evaluation

NVIDIA is hiring a Robotics Research Engineer - Robot Simulation and Evaluation in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include PyTorch, JAX and AI agents.
Level classifies it as a senior role.
Level lists 2,700+ other open roles at NVIDIA.

AI in this role

pytorchjax

ai-agents

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. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, encouraging environment where we all work together to advance the frontiers of accelerated computing.

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. In this role, 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. This mission builds on NVIDIA's history of creating virtual worlds using its groundbreaking technology on photorealistic rendering and physics simulation technologies.

What you'll be doing:

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.

What we need to see:

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.).

Ways to stand out from the crowd:

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.

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

How we rate this

Robotics Research Engineer - Robot Simulation and Evaluation at NVIDIA rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Robotics Research Engineer - Robot Simulation and Evaluation is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $184k-$288k a year.
The role is based in US, CA, Santa Clara.
The job was posted on August 18, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsPyTorchJAX

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through how you've used PyTorch in your day-to-day work.
What are the limits of JAX that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: AI agents, PyTorch, and JAX. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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