System Software Engineer – Data Center GPU Compute Diagnostics

Details

We are seeking a system software engineer to work on next-generation Data Center GPU diagnostics for rack-scale AI supercomputer systems. The charter is to build applications and compute workloads that test and heavily stress GPU compute engines, HBM memory, cache hierarchy, PCIe/NVLink interfaces, power delivery, and thermal behavior, and to use those applications in silicon/system bring-up along with packaging such tools for manufacturing and customer use. You will partner with a senior engineer leading the team's CUDA kernel and GEMM diagnostics work, owning well-scoped pieces of the codebase end-to-end while ramping on GPU microarchitecture and silicon characterization.

Good interpersonal skills are required as this role involves close collaboration with hardware architecture, silicon validation, manufacturing, and field teams. The engineer will grow their knowledge of operating systems, computer architecture, GPU memory, voltage/frequency behavior, thermal limits, high-speed buses, and modern AI development and analysis tools to efficiently validate and test next-generation processors and systems.

Responsibilities

• Work closely with hardware architecture, driver, manufacturing, and field teams through the product development lifecycle of rack-scale AI systems.
• Implement and maintain CUDA/C++ diagnostic workloads and software infrastructure used in chip development, validation, productization, and field triage.
• Write and tune GPU compute tests that stress Tensor Cores, SMs, L2/cache hierarchy, HBM memory, and related power/thermal operating points.
• Implement and tune GEMM-style diagnostic workloads, including tests combined with additional load in NVLink, PCIe, or CPU subsystems.
• Contribute to higher-level AI workload tests, including PyTorch-based large model workloads that stress GPUs, memory, interconnects, thermals, and system software under realistic rack-scale AI use cases.
• Bring up and validate new hardware features with pre-beta GPU drivers, low-level diagnostic software, and system telemetry, under guidance from the technical lead.
• Triage and debug failures involving ECC, HBM behavior, thermal limits, voltage/frequency margining, and PCIe/NVLink errors.

Requirements

• BS or MS degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
• 5+ years of system software, GPU software, embedded software, or hardware validation experience.
• Experience writing low-level diagnostics and interacting with device firmware and hardware-level debuggers.
• Strong C/C++ and Python programming skills.
• Exposure to GPU architecture, CUDA kernels, GPU compute workloads, or related accelerator programming is strongly preferred.
• Working knowledge of memory systems, ECC behavior, and DMA engines.
• Familiarity with GEMM-style workloads.
• Awareness of voltage/frequency characterization, thermal testing, power stress, or related silicon validation concepts such as Vmin/Fmax and P-state testing.
• Experience using modern AI development and analysis tools to improve engineering velocity, including code development, debugging, and test creation.
• Strong problem solving and low-level debugging skills.

Benefits

• Base salary range: 152,000 USD - 241,500 USD (determined based on location, experience, and pay of employees in similar positions).
• Eligibility for equity and company benefits (see company benefits information).

Additional information

• Applications for this job will be accepted at least until May 24, 2026.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is an equal opportunity employer and provides a diverse work environment.