System Software Engineer – Data Center GPU Compute Diagnostics

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are seeking a system software engineer to develop low-level diagnostic software for next-generation data center GPUs and rack-scale AI systems. Our team builds software that exercises and validates complex hardware, including compute engines, memory and cache subsystems, NICs, PCIe and NVLink interfaces, power delivery, and thermal behavior. This role is well suited to an embedded, firmware, device-driver, hardware-validation, or systems software engineer who enjoys working close to hardware. Relevant experience may come from GPUs, CPUs, networking, storage, servers, embedded systems, or other complex silicon-based products. Prior GPU, CUDA, or GEMM experience is helpful but not required; you will have the opportunity to learn GPU architecture and programming while working with experienced engineers. You will own well-scoped components of the diagnostic software from design through implementation, validation, productization, and field support. You will collaborate with hardware architects, driver developers, silicon-validation engineers, manufacturing teams, and field engineers to bring up new hardware and diagnose difficult system failures. Join an exciting, rewarding, and fast-moving environment building the systems that power modern AI. What you’ll be doing: • Developing diagnostic and stress software in C/C++ and Python for complex hardware systems. • Interfacing with hardware blocks, firmware, Linux device drivers, registers, telemetry, and low-level debugging tools. • Bringing up and validating new silicon and system features using pre-production hardware and software. • Creating targeted tests for compute engines, memory and cache subsystems, DMA engines, PCIe/NVLink interfaces, power, and thermal behavior. • Investigating hardware and software failures involving memory errors, ECC, data integrity, performance, thermals, voltage/frequency behavior, and high-speed interfaces. • Contributing to diagnostic and stress workloads ranging from low-level tests for GPU hardware to higher-level AI workloads, with opportunities to develop expertise in CUDA programming, GEMM-style compute, NCCL, and PyTorch-based workloads. • Using modern development and analysis tools, including AI-assisted tools where appropriate, to accelerate coding, debugging, test creation, and failure analysis. What we need to see: • BS or MS degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent experience. • 2+ years of experience in embedded software, firmware, Linux device drivers, systems software, hardware validation, diagnostics, or silicon bring-up. • Strong programming skills in C and C++, plus working proficiency in Python. • Experience developing software that interacts with hardware, firmware, device drivers, hardware registers, or low-level interfaces. • Experience creating diagnostics, validation tests, stress tests, manufacturing tests, or other software used to isolate hardware or system failures. • Understanding of fundamental computer architecture concepts such as memory, caches, interrup