Distinguished Resiliency and Safety Architect, GPU Diagnostics

About the role

We are now seeking a Resiliency and Safety Architect to support the development of GPU (graphical processing unit) diagnostics for Resiliency in the Datacenter and Functional Safety in Autonomous Vehicles and Robots.

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.

Requirements

Master’s or PhD degree in Computer Science, Computer Engineering, Electrical Engineering or 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.

Strong knowledge of hardware failure mechanisms that can result in incorrect computation.

Proficiency in C/C++, CUDA programming.

Scripting and automation with Python or similar.

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.

Be self-driven and results oriented.

Qualifications

Familiarity with GPU and SOC Architectures, Machine Learning/Deep Learning concepts.

Understanding factors causing silent data corruption in hardware.

Experience in embedded software development.

Skills

Experience with high performance libraries and writing hand-crafted kernels to create stress conditions to induce hardware failures.

Benefits

NVIDIA offers a competitive compensation package, including a base salary range of $320,000 - $488,750, depending on location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits.

Pay

The base salary range is $320,000 - $488,750.

Schedule

This posting is for an existing vacancy.