Distinguished Resiliency and Safety Architect, GPU Diagnostics

Details

Today, NVIDIA is 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. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work.

We are seeking a Resiliency and Safety Architect to support the development of GPU diagnostics for Resiliency in the Datacenter and Functional Safety in Autonomous Vehicles and Robots. You will be part of a team developing diagnostics for GPUs and SoCs used in AI datacenters, automotive functional safety, and robotics, and will collaborate with architecture, RTL, and verification teams.

Responsibilities

• Design, develop, and maintain a diagnostics software suite to efficiently stress test NVIDIA GPUs and SoCs to identify hardware defects, including defects that cause silent data corruption. Tests will run in large-scale deployments of datacenter GPUs and safety SoCs in package/board/rack configurations spanning GPUs, CPUs, and networking SoCs.
• Address coverage gaps in the NVIDIA diagnostic suite flagged by silicon failures on customer workloads or test suites; enhance diagnostics to improve repeatability of failures and optimize test time.
• Create tests for GPUs in automotive functional safety contexts, including low-level routines to exercise instruction sets, memory subsystems, and interrupt mechanisms, in compliance with ISO 26262 and related safety standards.
• Study silent data corruption, intermittent faults, and hard-to-reproduce field failures (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.

Requirements

• Master’s or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related degree, or equivalent experience.
• At least 15+ years of relevant experience.
• Ability to reason across hardware/software boundaries to debug complex system-level issues.
• In-depth understanding of the architecture and micro-architecture of high-performance computing systems and strong knowledge of hardware failure mechanisms that can result in incorrect computation.
• Proficiency in C and C++ and CUDA programming.
• Scripting and automation experience with Python or similar languages.
• Understanding of the software development life cycle, from requirements to testing closure and maintenance, including creating customer releases and documentation.
• Excellent interpersonal skills and ability to collaborate with on-site and remote teams.
• Strong debugging and analytical skills; self-driven and results oriented.

Ways to stand out from the crowd

• Familiarity with GPU and SoC architectures, and machine learning / deep learning concepts.
• Understanding factors causing silent data corruption in hardware.
• Ability to use high-performance libraries and write hand-crafted kernels when necessary to create stress conditions to induce hardware failures.
• Experience in embedded software development.

Benefits & Compensation

• Base salary range: 320,000 USD - 488,750 USD (determined based on location, experience, and pay of employees in similar positions).
• Eligible for equity and benefits (link provided in original posting).
• Applications accepted at least until February 27, 2026.

NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. NVIDIA uses AI tools in its recruiting processes.