We are seeking an exceptional hands-on engineer to help our partners and customers make demanding physics and robotics simulation workloads run exceptionally well on NVIDIA platforms. You will work at the intersection of algorithms, mathematics, GPU architecture, and production software to find the true limits of real applications and turn that understanding into durable code and actionable feedback for NVIDIA engineering teams.
This role is for someone with a recognizable technical body of work: not someone who merely used advanced systems, but someone who took stewardship of one and made it substantially better.
What you'll be doing:
Help our partners and customers establish and execute performance strategies for important physics, robotics simulation, and computational-engineering workloads on NVIDIA GPUs.
Build rigorous benchmarks and performance models, profile customer applications from system architecture through GPU kernels, and identify the actual limiting factors.
Work with partner developers to improve algorithms, data structures, memory layouts, and parallel execution. When evidence points to an NVIDIA platform bottleneck, collaborate with the owning engineering team rather than duplicating its role.
Understand and apply knowledge of reinforcement learning, robotic kinematics simulation setup and simulation validation to the challenges that our partners bring.
Write and upstream production C++, CUDA, Python, and domain-specific GPU code into simulation platforms, partner applications, and reusable reference implementations.
Work across developers, NVIDIA architecture and software teams, and open technical communities to make the improvement last beyond a single engagement.
What we need to see:
12+ years of relevant experience
A degree in Computer Science, Applied Mathematics, Physics, Mechanical Engineering, Computational Science, or a related field—or equivalent experience.
Publicly inspectable stewardship of a consequential open-source engine, library, standard, benchmark, or software framework. Your implementation and technical leadership must be visible in the artifact itself.
A record of delivering large, reproducible performance improvements in production numerical, simulation, graphics, CAE, robotics, or scientific-computing systems.
Expert modern C++ and GPU parallel-programming ability, backed by strong foundations in mathematics, physics, numerical methods, geometry, or performance modeling.
Ways to stand out from the crowd:
Deep experience with physics engines, numerical solvers, geometry processing, differentiable simulation, or large-scale batched simulation.
Experience with CUDA, Warp, Newton, PhysX, Isaac Sim, Isaac Lab, MuJoCo, JAX, or comparable accelerated-computing systems.
A history of carrying important technical work beyond the breakthrough through integration, maintenance, documentation, and the success of other developers.
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 or more years of relevant experience
- Degree in Computer Science, Applied Mathematics, Physics, Mechanical Engineering, Computational Science, or related field, or equivalent experience
- Publicly inspectable stewardship of a consequential open-source engine, library, standard, benchmark, or software framework
- Record of delivering large, reproducible performance improvements in production numerical, simulation, graphics, CAE, robotics, or scientific-computing systems
- Expert modern C++ and GPU parallel-programming ability
- Strong foundations in mathematics, physics, numerical methods, geometry, or performance modeling
- Deep experience with physics engines, numerical solvers, geometry processing, differentiable simulation, or large-scale batched simulation
- Experience with CUDA, Warp, Newton, PhysX, Isaac Sim, Isaac Lab, MuJoCo, JAX, or comparable accelerated-computing systems
- History of carrying technical work through integration, maintenance, documentation, and success of other developers
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.”
