System Software Engineer – Data Center Compute Diagnostics

NVIDIA•Durham, NC

6d•$152,000 - $241,500

About The Position

NVIDIA is 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.

Requirements

BS or MS degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent experience.
5+ 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, interrupts, DMA, buses, and device I/O.
Strong debugging and problem-solving skills, including the ability to investigate failures across hardware and software boundaries.
Ability to take ownership of a well-scoped problem and drive it to completion while collaborating with a technical lead and multi-functional teams.
Good written and verbal communication skills.

Nice To Haves

Prior GPU, CUDA, or GEMM experience is helpful but not required

Responsibilities

Developing diagnostic and stress software in C/C++ and Python for complex hardware systems.
Collaborating 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.