- Robot type
- Robot AI and Software
- Location
- Santa ClaraCaliforniaUSA
- Job type
- Manufacturing
- Posted
- Sep 14, 2026
Full-time
Senior Manager, Robotics Quality Assurance
Job description
We are looking for a Senior Manager, Robotics Quality Assurance to join our SW QA team! You will part of a team that drives all Quality and Innovation for the Nvidia Robotics team! You’ll create engineering processes and build relationship bridges to ensure that the highest industry standards are met.
Job responsibilities
- Define and drive the overall test engineering strategy for our robotics products, establishing an engineering-focused approach to quality encompassing design for scalable test frameworks, tools, and methodologies and…
- Deliver test automation development for “On-Robot Hardware & Software” and embedded software running on our NVIDIA Jetson AGX Thor platform encompassing sensor integration validation, real-time performance, and…
- Architect and implement rigorous test plans to validate “AI Foundation models”, like Isaac GR00T, focused on performance, safety, and reliability in real-world scenarios.
- Build and maintain the test infrastructure within our “Simulation & Digital Twins” environments, Isaac Sim and Isaac Lab, developing automated tests verifying physics engine accuracy and the transferability of learned…
- Oversee test automation development for the full “Robotics Software Stack”, including Isaac ROS, and its integration with other robotic components.
- Architect, build, and maintain the test infrastructure for a humanoid reference platform showcasing the power of NVIDIA's technology and develop testing methodologies bridging the "sim-to-real" gap, creating a…
- You'll lead the design of complex test scenarios in Isaac Sim/Lab that use generative AI to stress-test robot policies, ensuring that models trained in simulation (using Isaac GR00T) perform reliably on real physical…
- Lead design of complex test scenarios in Isaac Sim/Lab that use generative AI to stress-test robot policies, ensuring that models trained in simulation (using Isaac GR00T) perform reliably on real physical hardware.
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