GPU Diagnostics: Resiliency & Safety Architect

NVIDIA; Santa Clara (CA); On-site; USD 320,000 - 488,750; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Distinguished Resiliency and Safety Architect to lead the development of GPU diagnostics for Datacenter resiliency and autonomous vehicle safety. The role focuses on stress-testing GPUs/SoCs, reducing silent data corruption, and collaborating with hardware/software teams across NVIDIA architectures.

The position requires deep expertise in C/C++, CUDA, Python, and a strong product development mindset.

Qualifications

• Master’s or PhD degree in Computer Science, Computer Engineering, Electrical Engineering or closely related field.
• At least 15+ years of relevant experience.
• Ability to reason across hardware/software boundaries to debug complex system-level issues.
• Strong knowledge of high-performance computing architectures and hardware failure mechanisms.
• Proficiency in C/C++, CUDA programming.
• Scripting and automation with Python.
• Understanding of the software development life cycle, including releases and documentation.
• Excellent interpersonal skills and collaboration with on-site and remote teams.
• Strong debugging and analytical skills.

Responsibilities

• Design, develop, and maintain diagnostics software suite to efficiently stress test NVIDIA GPUs and SOCs to identify hardware defects, including defects that cause silent data corruption.
• Address coverage gaps in NVIDIA diagnostic suite flagged by silicon failures on customer workloads or test suites. Enhance diagnostics to improve repeatability of failures detected and optimize test time.
• Tests for GPUs in automotive functional safety contexts should include low-level routines to exercise instruction sets, memory subsystems and interrupt mechanisms, in compliance with ISO 26262 and related safety standards. Collaborate with architecture, RTL, and verification teams to ensure safety coverage, correctness, and robustness across GPU generations.
• Study silent data corruption, intermittent faults, and hard-to-reproduce failures in the field, including customer returns (RMAs), to establish root causes, and improve detection by diagnostics.
• Support deployment of diagnostics in pre-production qualification environments as well as large-scale production usages.

Skills

Hardware/Software boundary reasoning

Debugging

Python scripting

C/C++ / CUDA

Collaboration

Self-driven mindset

Education

Master’s or PhD in CS/CE/EE

Job description

NVIDIA is seeking a Distinguished Resiliency and Safety Architect to lead the development of GPU diagnostics for Datacenter resiliency and autonomous vehicle safety. The role focuses on stress-testing GPUs/SoCs, reducing silent data corruption, and collaborating with hardware/software teams across NVIDIA architectures.

The position requires deep expertise in C/C++, CUDA, Python, and a strong product development mindset.