GPU System Performance Architect

Nvidia

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Quick summary

Work type: On-site
Location: Santa Clara, CABoulder, COHillsboro, OR
Salary: $224,000–$356,500 / yr
Employment: Full-time
Posted: 6 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $227k

This role $290k

$163k $377k

below market most similar roles pay here above market

This role pays more than 89% of similar roles. Most pay $196,750–$256,950 — the blue band above. At the midpoint, this role pays about $290k versus about $227k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1805 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1196 roles with salary data.

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At a glance

TL;DR · GPU System Performance Architect

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The GPU System Performance Architect joins the Architecture group to design and develop next-generation GPU-accelerated computing systems. The role involves developing innovative processor and system architectures to advance GPU-accelerated cloud computing. Key responsibilities include analyzing trade-offs in system performance, cost, and efficiency by developing analytical models, simulators, and data visualization tools. The architect must analyze hardware and software interactions within large-scale data center deployments and collaborate with software, product, and business teams. Required skills include deep knowledge of computer architecture, analytical performance modeling, simulation, profiling, and analysis. Candidates should possess expertise in data analysis, visualization, and parallel programming models. The work focuses on optimizing GPU computing for deep learning, data analytics, and high-performance computing within virtualized cloud environments and PCIe or IO-centric workloads.

Skills

Computer Architecture Deep Learning High Performance Computing Performance Modeling Simulation Data Visualization Parallel Programming PCIe Cloud Computing AI Neural Networks Profiling

What you'll do

Develop innovative processor and system architectures for GPU-accelerated cloud computing.
Analyze trade-offs in system performance, cost, and efficiency using analytical models.
Build simulators and data visualization tools to evaluate system performance.
Analyze hardware and software interactions in large-scale data center deployments.
Guide the strategic direction of GPU-accelerated cloud computing across various departments.
Perform performance modeling, characterization, and optimization for PCIe and IO-centric workloads.

What we're looking for

Master's or PhD in Computer Science, Electrical Engineering, or Computer Engineering (or equivalent experience).
10 years of relevant work or research experience.
Excellent mathematical and analytical skills.
Deep knowledge of computer architecture.
Experience with analytical performance modeling, simulation, profiling, and analysis.
Strong communication, organizational, and interpersonal skills.
Background in data center/cloud computing design with experience crafting hardware for virtualized environments (preferred).
Expertise in data analysis and visualization (preferred).

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