System Software Engineer - GPU

NVIDIA•Santa Clara, CA

About The Position

We are seeking a System Software Engineer to work on next-generation computing and graphics products. Our charter is to build low level GPU testing frameworks to validate GPUs early in the life cycle. The best candidates will have strong C++ programming skills, thorough knowledge of GPU concepts and algorithms, a solid foundation of systems software with emphasis on OS fundamentals, and a deep understanding of current generation hardware architecture. Excellent interpersonal skills and a dedication to meticulous engineering practices are a requirement. As a system software engineer, you will use your knowledge of operating systems, algorithms, and computer architecture to provide robust and efficient solutions to validate and test next generation processors.

Requirements

BS or MS degree in one of the areas of Electrical Engineering, Computer Engineering, Computer Science (or equivalent experience)
5+ years proven experience in a related hardware/software position
Strong C/C++ programming skills
Understanding of PC architecture, and ability to work close to the hardware
Very strong problem solving and debugging skills
Ability to self-manage, show leadership, and have good interpersonal skills

Nice To Haves

Background with Parallel Computing, PCIE, Nvlink or server product technologies like Infiniband, Ethernet is a plus.
Experience utilizing AI tools to improve velocity while delivering the highest quality results.
Familiarity with modern AI-assisted software development workflows (e.g., AI-based code generation, test generation, debugging, or analysis).
Previous experience of working on a large system software code base is preferable

Responsibilities

Working closely with architecture, hardware and driver teams through the product development life cycle of computing and graphics processors, as well as compute products.
Responsible for crafting software tools and infrastructure required for new chip development, validation, and productization.
Architect and develop foundational capabilities required for Data Center and Consumer GPU diagnostics.
Assess new hardware features and architect manufacturing diagnostic tests using pre-beta CUDA and Vulkan extensions.
Explore ways to use high level compute & graphics programming APIs to stress specific units and flows at a GPU and system level.
Leverage AI-assisted development tools to accelerate test creation, debugging, and analysis while maintaining high code quality.
Apply AI/ML techniques to improve test coverage, failure triage, log analysis, and overall validation efficiency.
Collaborate with the team to identify opportunities for agent-based or automated workflows that improve developer velocity and reliability.