We are now looking for a Principal Datacenter Resiliency Architect, RAS Features and Modeling! 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. Come join the team and see how we can make a lasting impact on the world.
We are now seeking a Resiliency Architect to support the development and validation of GPU (graphical processing unit) hardware and software resiliency features, including modeling reliability and availability from component to datacenter level. In this role, you will be a key member of a team of innovators, challenging the status quo and pushing beyond boundaries. You will have the opportunity to impact the industry's leading Datacenter GPUs and SOCs powering product lines for the growing field of artificial intelligence (AI) and high-performance computing (HPC).
What you'll be doing:
Architect hardware and software Resiliency features to improve system Reliability, Availability, Serviceability (RAS), and performance in the Datacenter.
Model and analyze RAS metrics like Failures in Time (FIT) for permanent and transient errors, and Availability from GPU to Rack to Datacenter. Use models to identify gaps and drive RAS improvements.
Analyze field data on hardware interruptions and permanent failures; enhance RAS models to better correlate to field data; and ensure optimal fault attribution, containment, and recovery for hardware errors
Collaborate with architects, unit designers and software engineers to ensure alignment of design and verification requirements to architecture specifications.
Develop and implement comprehensive architecture verification testplans for resiliency features
Execute architecture testplans by developing test content, working with Software and Architecture teams to enable, run, and debug tests on Architecture models. Support test debug on RTL, emulation, and silicon.
Run simulations to analyze Architectural Vulnerability Factor (AVF) and Liveness of on-die memory, flip-flops, and latches.
What we need to see:
PhD degree in Computer Engineering, Electrical Engineering or closely related degree or equivalent experience.
At least 10+ years of relevant experience.
Strong Understanding of GPU and Networking Architectures, Computer Architecture basics (including caches, coherence, buses, direct memory access, etc.); Machine Learning/Deep Learning concepts.
Strong knowledge and industry expertise in either GPU hardware architecture or RAS features or both.
Proficiency in developing Reliability (FIT) models, AVF estimation.
Good understanding of Availability concepts, ECC/parity/CRC strategies.
Strong understanding of hardware/software interactions for error handling.
Scripting and automation with Python or similar.
Excellent interpersonal skills and ability to collaborate with on-site and remote teams.
Strong debugging and analytical skills.
Ways to stand out from the crowd:
Experience with network and high-speed interface resiliency.
Proven experience leading and delivering RAS features across hardware, software, and infrastructure teams
Strong understanding of resiliency and reliability trade-offs in AI data centers, including failure modes, mitigation strategies, and impact on large-scale training/inference workloads
NVIDIA’s invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI - the next era of computing - with the GPU acting as the brain of AI factories, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. Do you love the challenge of crafting the most resilient high-performance silicon possible? If so, we want to hear from you! Come, join our Resiliency and Safety Architecture team and help build the resilient, highly available, cost-effective computing platform driving our success in this exciting and rapidly growing field.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until February 27, 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.
