Senior System Software Engineer – Data Center Compute Diagnostics

Details

We are seeking a senior system software engineer to lead technically and own key parts of low-level diagnostic software supporting next-generation data center GPUs and rack-scale AI systems. The team builds software that exercises and validates complex hardware, including processing units, storage and cache architectures, NICs, PCIe and NVLink interfaces, power delivery, and thermal behavior.

This hands-on software development role involves architecting, implementing, debugging, and maintaining diagnostic software through validation, productization, and field support. You will make substantial individual code contributions, lead complex development efforts, mentor other engineers, and collaborate with hardware architects, driver developers, silicon-validation engineers, manufacturing teams, and field engineers to bring up new hardware and diagnose difficult system failures.

Prior GPU, CUDA, or GEMM experience is helpful. Deep experience developing low-level software for complex hardware systems is required. Relevant backgrounds may include GPUs, CPUs, networking, storage, servers, embedded systems, or other complex silicon-based products.

Responsibilities

• Architect and develop diagnostic and stress software in C, C++, and Python for complex hardware systems.
• Lead development efforts across multiple engineers, break ambiguous problems into actionable work, and mentor engineers in low-level software development and debugging.
• Interface with hardware blocks, firmware, Linux device drivers, registers, telemetry, and low-level debugging tools.
• Assess new hardware features and define diagnostic and stress strategies for engineering validation, manufacturing, product qualification, and field use.
• Design targeted tests for compute engines, memory and cache subsystems, DMA engines, NICs, PCIe and NVLink interfaces, power, and thermal behavior.
• Develop diagnostic and stress workloads ranging from low-level GPU hardware tests to higher-level AI workloads using CUDA programming, GEMM-style compute, NCCL, and PyTorch.
• Investigate complex hardware and software failures involving memory errors, ECC, data integrity, performance, thermals, voltage and frequency behavior, and high-speed interfaces.
• Use modern development and analysis tools, including AI-assisted tools where appropriate, to accelerate coding, debugging, test creation, and failure analysis.

Requirements

• BS or MS degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent experience.
• 12+ years of experience in embedded software, firmware, Linux device drivers, systems software, hardware validation, diagnostics, or silicon bring-up.
• Experience providing technical leadership for a complex software component or project, including coordinating work among engineers and mentoring others.
• Strong programming skills in C and C++, plus working proficiency in Python.
• Extensive experience developing software that interacts with hardware, firmware, device drivers, hardware registers, or other low-level interfaces.
• Background with PCIe, NVLink, or networking technologies such as Ethernet or InfiniBand.
• Strong understanding of computer architecture concepts, including memory systems, caches, interrupts, DMA, buses, device I/O, bandwidth constraints, and hardware error behavior.
• Experience debugging complex failures across hardware, firmware, device drivers, operating systems, and applications.
• Ability to define technical direction, make sound engineering tradeoffs, and drive ambiguous problems through completion across organizational boundaries.
• Excellent written and verbal communication skills, including the ability to communicate effectively with hardware architects, software engineers, manufacturing teams, field engineers, and technical leadership.

Benefits

NVIDIA offers highly competitive salaries, equity, and a comprehensive benefits package.

Applications for this job will be accepted at least until August 3, 2026. NVIDIA uses AI tools in its recruiting processes and is committed to fostering an inclusive work environment and providing equal employment opportunities.