TieTalent
Join to apply for the
Senior Datacenter Resiliency Architect
role at
TieTalent 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.
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 (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.
What we need to see
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/SystemVerilog RTL simulations and debugging; ability to set up test benches and integrate components is a plus.
Programming with CUDA is a plus.
Company/role notes 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.
#J-18808-Ljbffr
Senior Datacenter Resiliency Architect
role at
TieTalent 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.
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 (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.
What we need to see
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/SystemVerilog RTL simulations and debugging; ability to set up test benches and integrate components is a plus.
Programming with CUDA is a plus.
Company/role notes 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.
#J-18808-Ljbffr