Senior Datacenter Resiliency Architect at NVIDIA

Santa Clara, California, United States

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$184,000 – $356,500Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, High-Performance Computing, DatacenterIndustries

Requirements

Master’s or PhD degree in Computer Engineering, Electrical Engineering, or closely related degree or equivalent experience
At least 5+ years of relevant experience
Familiarity with 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 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

Responsibilities

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 for permanent and transient errors, and 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 testplans for resiliency features
Execute Architecture Testplan 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 and Liveness of on-die memory, flip-flops, and latches
Develop CUDA software diagnostics kernels for to run on clusters of NVIDIA GPUs and identify potential hardware issues
Develop and automate fault models to simulate various fault types (e.g., transient faults, stuck-at faults) in gate-level netlist, RTL, architectural model, silicon and other environments

Skills

GPU Architecture

Networking Architectures

Computer Architecture

RAS

Machine Learning

Deep Learning

Python

C/C++

Architecture Modeling

Debugging

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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