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Nvidia Diagnostic Software Jobs (NOW HIRING)

Nvidia

OR · On-site

$166K/yr

Using the most advanced GPUs and NVIDIA proprietary software, GeForce NOW transforms the gaming ... Proven experience in System Software, Diagnostic Software, Hardware Reliability of GPU, CPU, Memory ...

Nvidia

Senior Board Test Engineer

Santa Clara, CA · On-site

... diagnostic software. * Support the development of test content and solutions in Python ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Nvidia

System Test Engineer

Santa Clara, CA · On-site

Debug complex hardware and software issues during build phases * Contribute to automated diagnostic ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Nvidia

Senior System Test Engineer

Santa Clara, CA · On-site

... diagnostic software. * Review and provide feedback for DFT in the early design stages. * Debug ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Nvidia

System Test Engineer

Santa Clara, CA · On-site

... NVIDIA. What you'll be doing: * Partner with internal and external hardware and software teams to ... diagnostic software. * Regular tester and test facility status reporting and improvement ...

Nvidia

Senior Thermal Design Engineer

Santa Clara, CA · On-site

These methods and processes are developed within NVIDIA's thermal team. Part of your responsibility ... testing with specific diagnostic software, summarizing data, disassembling, modifying and ...

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All JobsNvidia Diagnostic Software Jobs

Nvidia Diagnostic Software information

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$15

$61

$87

How much do nvidia diagnostic software jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for nvidia diagnostic software in the United States is $61.73, according to ZipRecruiter salary data. Most workers in this role earn between $52.40 and $69.23 per hour, depending on experience, location, and employer.

What is the difference between Nvidia Diagnostic Software vs GPU Technician?

AspectNvidia Diagnostic SoftwareGPU Technician
Primary RoleDiagnoses and tests Nvidia graphics cards using specialized software toolsRepairs, maintains, and replaces GPU hardware components
Required SkillsKnowledge of Nvidia software, troubleshooting, and diagnostic proceduresHardware repair, soldering, component replacement, technical troubleshooting
Work EnvironmentSoftware labs, technical support centers, remote diagnosticsHardware repair shops, electronics labs, manufacturing facilities
CertificationsIT certifications, Nvidia certifications, hardware troubleshooting coursesElectronics certifications, soldering certifications, hardware repair training

While Nvidia Diagnostic Software focuses on software-based diagnostics and testing of Nvidia GPUs, GPU Technicians handle physical hardware repairs and maintenance. Both roles require technical knowledge but differ in their primary tasks and work environments. Understanding these differences helps employers and professionals choose the right career path or service for GPU-related issues.

What is Nvidia Diagnostic Software?

Nvidia Diagnostic Software refers to specialized tools and utilities developed by Nvidia to help users and IT professionals monitor, troubleshoot, and optimize Nvidia GPUs and related hardware. These tools can detect hardware issues, report system health, and provide insights into driver or configuration problems. They are commonly used in both gaming and professional environments to ensure optimal GPU performance and stability. Some popular diagnostic tools include Nvidia System Management Interface (nvidia-smi) and Nvidia Control Panel. Using these tools can help identify faults early and maintain system reliability.

What are the key skills and qualifications needed to thrive as an Nvidia Diagnostic Software Engineer, and why are they important?

To thrive as an Nvidia Diagnostic Software Engineer, you need strong programming skills in C/C++, experience with hardware diagnostics, and a degree in computer engineering or a related field. Familiarity with debugging tools, embedded systems, and Nvidia’s CUDA platform is often required, along with experience using version control systems like Git. Analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with cross-functional teams and troubleshooting complex issues. These skills ensure that hardware and software function reliably, contributing to Nvidia’s high-quality product standards.

What are some common challenges faced by professionals working in Nvidia Diagnostic Software roles?

Professionals in Nvidia Diagnostic Software roles often encounter challenges such as staying updated with rapidly evolving hardware architectures and ensuring compatibility across a wide range of GPU models. Debugging complex issues that may involve both hardware and software layers requires strong analytical skills and meticulous attention to detail. Additionally, collaborating effectively with cross-functional teams—including hardware engineers, driver developers, and QA testers—is essential for timely and robust diagnostic tool development. Adapting to new releases and maintaining thorough documentation are also key aspects of the role.
Infographic showing various Nvidia Diagnostic Software job openings in the United States as of June 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $128,400 per year, or $61.7 per hour.
Senior System Software Engineer - Data Center GPU Compute Diagnostics

Senior System Software Engineer - Data Center GPU Compute Diagnostics

Nvidia Corporation

Durham, NC • On-site

$118K - $156K/yr

Full-time

Posted 22 days ago

Job description

We are seeking a senior system software engineer to work on next-generation Data Center GPU diagnostics for rack-scale AI supercomputer systems. Our 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. The best candidates will have strong experience writing low-level diagnostic, performance, or stress software for complex hardware systems, ideally including experience with GPUs, CUDA kernels, GEMM-style workloads, NCCL communication patterns, CPUs, NICs or high-speed interconnects such as PCIe.
Excellent interpersonal skills are required as this role will involve mentoring other engineers and collaborating with hardware architecture, silicon validation, manufacturing and field teams. In addition, the engineer will extensively use 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. Join an exciting, rewarding and fast paced environment!
What you'll be doing:
  • Working closely with hardware architecture, driver, manufacturing and field teams through product development lifecycle of rack-scale AI systems.
  • Responsible for crafting CUDA/C++ diagnostic workloads and software infrastructure required for new chip development, validation, productization, and field triage.
  • Designing and implementing GPU compute tests that stress Tensor Cores, SMs, L2/cache hierarchy, HBM memory, and related power/thermal operating points.
  • Developing and tuning GEMM-style diagnostic workloads, including tests combined with additional load in NVLink, PCIe or CPU subsystems.
  • Developing and integrating higher-level AI workload tests, including PyTorch-based large model workloads to stress GPUs, memory, interconnects, thermals, and system software under realistic rack-scale AI use cases.
  • Assessing new hardware features and architecting manufacturing and field diagnostic tests using pre-beta GPU drivers, low-level diagnostic software, and system telemetry.
  • Debugging failures involving ECC, HBM behavior, thermal limits, voltage/frequency margining and PCIe/NVLink errors.

What we need to see:
  • BS or MS degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
  • 12+ years of system software, GPU software, embedded software, or hardware validation experience.
  • Experience driving technical work across multiple engineers, mentoring others, or leading development of a complex software component.
  • Experience writing diagnostics and stress tests that interface to low-level hardware drivers and hardware registers.
  • Strong C/C++ and Python programming skills.
  • Experience with Linux device drivers, CUDA kernels, GPU compute workloads, or related accelerator programming is strongly preferred.
  • Understanding of memory systems, ECC behavior, cache hierarchy, bandwidth bottlenecks, and hardware failure signatures.
  • Understanding of GEMM-style workloads and how workload shape, precision, runtime, and verification affect compute stress, power, memory, and thermal behavior.
  • Experience with voltage/frequency characterization, thermal testing, power stress, or related silicon validation concepts such as Vmin/Fmax and P-state testing.
  • Background with PCIe, NVLink, or networking technologies such as InfiniBand and Ethernet.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 22, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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About Nvidia

Sourced by ZipRecruiter

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.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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