Job description

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. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until September 13, 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.

Requirements

Must-haves

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.
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.
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.
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.
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 .
Applications for this job will be accepted at least until September 13, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonai

Platform: workday
Effort: long