We are looking for a senior technical leader to own the engineering loop between physical robots and simulation. You will determine why simulated and real behavior differ, build the systems needed to measure and model that difference, and drive the work until it improves robot performance for our partners and the broader robotics developer community.
This is a hands-on individual-contributor leadership role, not a people-management position. You will set direction, write production software, build and run physical experiments, and lead multi-functional contributors through technical influence rather than formal reporting lines.
What you'll be doing:
Own DevTech's sim-to-real and real-to-sim function: experiment design, instrumentation, data capture, system identification, model integration, and validation on hardware.
Build production-quality C++ and Python software for measurement, modeling, simulation, benchmarking, and regression testing.
Establish quantitative metrics and experiments that isolate the causes of simulation error and show whether a change materially improved the real system.
Turn evidence from partner robots into reusable workflows and improvements for NVIDIA's robotics and simulation platforms.
Lead contributors across disciplines without formal authority, create clarity, and remain accountable through integration and sustained use.
What we need to see:
12+ years of relevant experience
A degree in Mechanical Engineering, Aerospace Engineering, Robotics, Controls, Computer Science, Applied Mathematics, Physics, or a related field—or equivalent experience.
A consequential technical project you personally built, led, and maintained. Publicly inspectable work is the strongest evidence; a major closed-source production system also counts when its shipped impact and your contribution can be verified without disclosing confidential information.
End-to-end ownership of a hard-tech system in robotics, aerospace, automotive, industrial automation, scientific instrumentation, or a comparable field—from physical measurement and modeling through working software and validated results.
Expert C++ and Python software engineering, grounded in first-principles knowledge of dynamics, controls, system identification, numerical methods, applied mathematics, or closely related areas.
Ways to stand out from the crowd:
Direct experience characterizing robot actuators, sensors, contact, latency, or control behavior with fit-for-purpose instrumentation.
Experience with Isaac Sim, Isaac Lab, Newton, Warp, MuJoCo, Drake, PhysX, ROS/ROS 2, or comparable platforms.
Experience turning a successful one-off experiment into a maintained tool, benchmark, model, or workflow used by other engineers.
You will also be eligible for equity and benefits.
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.Skills Required
- 12+ years of relevant experience
- Degree in Mechanical Engineering, Aerospace Engineering, Robotics, Controls, Computer Science, Applied Mathematics, Physics, or a related field, or equivalent experience
- A consequential technical project personally built, led, and maintained
- End-to-end ownership of a hard-tech system in robotics, aerospace, automotive, industrial automation, scientific instrumentation, or a comparable field
- Expert C++ and Python software engineering skills
- First-principles knowledge of dynamics, controls, system identification, numerical methods, applied mathematics, or closely related areas
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
