Description
We're looking for a senior technical leader to help raise the fidelity, robustness, and practical value of our engineering simulation stack for robotics, automation, and industrial digital twins. This role involves designing and developing physically based simulation systems for robotics, industrial automation, and digital twins. You'll collaborate with teams across PhysX, Newton, Omniverse, Isaac Sim, and Isaac Lab to bring higher-fidelity simulation capabilities into NVIDIA's robotics and simulation platforms.
Responsibilities:
- Design and develop physically based simulation systems for robotics, industrial automation, and digital twins.
- Collaborate with teams across PhysX, Newton, Omniverse, Isaac Sim, and Isaac Lab to bring higher-fidelity simulation capabilities into NVIDIA's robotics and simulation platforms.
- Develop and improve methods for multibody dynamics, contact and friction, flexible-body behavior, deformables, and numerical solvers.
- Integrate simulation with robotics and engineering workflows involving ROS 2, CAD and URDF pipelines, OpenUSD assets, HIL/SIL environments, and controller-development loops.
- Help scale advanced simulation algorithms on GPUs, mentor engineers, and provide technical leadership across the organization.
Requirements:
- B.Sc. (or equivalent experience) or M.Sc. or Ph.D. with 8+ years of experience in Computer Science, Computer Engineering, Robotics, Applied Math, Physics, or a related field.
- A track record of building or leading simulation software used in production engineering, robotics, industrial machinery, automotive, aerospace, manufacturing, or adjacent domains.
- Deep knowledge in several areas such as multibody dynamics, constrained systems, contact and friction, articulations, flexible bodies, cable or wire simulation, deformables, FEM, solver design, numerical integration, stiffness handling, or model reduction.
- Experience validating simulators against physical systems, including test correlation, calibration, HIL/SIL workflows, controller co-simulation, or similar methods.
- Working proficiency with robotics-system integration and mechanical-engineering toolchains, including ROS 2, Simulink, Simscape, and model pipelines based on CAD, URDF, MJCF, or OpenUSD.
- Interest in applying modern AI-assisted and agentic development workflows to large-scale simulation systems.
Preferred qualifications include experience with GPU accelerated computing, reinforcement learning, sim-to-real robotics workflows, or robotics simulation at scale, as well as publications in relevant venues.