Nvidia Senior Software Engineer – Robotics Validation Benchmarking 

United States, California 

130322198

What You’ll Be Doing:

• Design and own the development of robust benchmarking pipelines for SIL and HIL setups across NVIDIA’s robotics stack.

• Define key performance indicators and success metrics for evaluating robotic systems dedicated to perception, planning, and control.

• Develop automated testing frameworks that integrate with simulation environments and physical robots to assess system performance and reliability.

• Engage with versatile teams encompassing hardware, software, systems, and applied research to ensure alignment on evaluation goals and methodologies.

• Identify gaps in current testing infrastructure and propose solutions that improve coverage, scalability, and accuracy. Drive the benchmarking strategy for end-to-end evaluation of real-world robotic use cases, including performance under edge cases and long-tail scenarios.

• Mentor junior engineers and provide technical leadership across projects.

What We Need To See:

• Bachelor’s or Master’s degree in Robotics, Computer Science,Electrical/MechanicalEngineering or a related field or equivalent experience (PhD preferred).

• 8+ years of experience in robotics, embedded systems, or related domains with a focus on system validation, SIL/HIL, or benchmarking.

• Deep understanding of simulation frameworks (e.g., Isaac Sim, Gazebo, ROS2) and real-time testing environments.

• Strong programming skills in C++, Python, and experience with automated test frameworks.

• Shown proficiency in setting and tracking performance metrics for advanced technology systems.

• Experience working with robotic platforms (mobile robots, manipulators, drones, etc.) and physical system integration. Excellent interpersonal skills and a collaborative attitude.

Ways To Stand Out From The Crowd:

• Experience with NVIDIA platforms (Jetson, Isaac, Omniverse).

• Contributions to open-source robotics communities. Prior work on real-time safety validation, edge AI benchmarking, or AI model evaluation in robotics.

• A passion for creating reliable systems that bridge the gap between simulation and the real world.