Senior Datacenter Resiliency Architect

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We are seeking a Senior Datacenter Resiliency (RAS) Architect to support the development and validation of GPU hardware and software resiliency features. You will be a key member of a team of innovators, challenging the status quo and pushing beyond boundaries, with impact on the industry’s leading Datacenter GPUs and SOCs powering AI and HPC products.

• Architect hardware and software resiliency features to improve system Reliability, Availability, Serviceability (RAS), and performance in the Datacenter.
• Model and analyze RAS metrics (e.g., Failures in Time for permanent and transient errors, Availability from GPU to Rack to Datacenter); use models to identify gaps and drive RAS improvements.
• Collaborate with architects, unit designers, and software engineers to ensure alignment of verification requirements.
• Develop and implement comprehensive architecture verification test plans for resiliency features.
• Execute Architecture Test Plan by developing test content and enabling, running, and debugging tests on architecture models; support test debug on RTL, emulation, and silicon.
• Run simulations to analyze Architectural Vulnerability Factor and liveness of on-die memory, flip-flops, and latches.
• Develop CUDA software diagnostics kernels to run on clusters of NVIDIA GPUs to identify hardware issues.
• Develop and automate fault models to simulate various fault types (e.g., transient faults, stuck-at faults) in gate-level netlists, RTL, architectural models, silicon, and other environments.

• Master’s or PhD in Computer Engineering, Electrical Engineering, or closely related field, or equivalent experience.
• At least 5+ years of relevant experience.
• Familiarity with GPU and networking architectures, computer architecture basics (caches, coherence, buses, DMA), and machine learning/deep learning concepts.
• Strong knowledge and experience in GPU hardware architecture or RAS features, or both.
• Proficiency in developing architecture models.
• Scripting and automation with Python or similar; proficiency in C/C++.
• Excellent interpersonal skills and ability to collaborate with on-site and remote teams; strong debugging and analytical skills; self-driven and results oriented.
• Experience with resiliency and datacenter RAS or Verilog/System Verilog RTL simulations and debugging; ability to set up test benches and integrate components is a plus.
• Programming with CUDA is a plus.

NVIDIA’s work spans high-performance computing and AI computing—roles involve building resilient, high-availability computing platforms for AI, HPC, and data center workloads. NVIDIA is an equal opportunity employer; we do not discriminate on protected characteristics.