GPU System Performance Architect

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Santa Clara, CABoulder, COHillsboro, OR
Salary: $224,000–$356,500 / yr
Posted: 3 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $219k

This role $290k

$144k most similar roles pay here $379k

This role pays more than 92% of similar roles. Most pay $187,850–$250,000 — the shaded band above. At the midpoint, this role pays about $290k versus about $219k 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 899 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 886 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. This role focuses on developing innovative processor and system architectures to advance state-of-the-art GPU-accelerated cloud computing. The architect will analyze trade-offs in performance, cost, and efficiency by building analytical models, simulators, and data visualization tools while analyzing hardware and software interactions within large-scale data center deployments. Key responsibilities include collaborating with cross-functional teams to guide the direction of GPU-accelerated cloud computing. Required expertise includes computer architecture, analytical performance modeling, simulation, profiling, and analysis. The role specifically addresses technical challenges in GPU-accelerated deep learning, data analytics, and high-performance computing. Candidates should possess skills in parallel programming models and experience with PCIe and IO-centric workloads to optimize systems for virtualized environments and large-scale infrastructure.

Skills

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

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.
Create simulators and data visualization tools to evaluate architectural designs.
Analyze hardware and software interactions within large-scale data center deployments.
Guide the strategic direction of GPU-accelerated cloud computing across various internal teams.
Perform performance modeling, characterization, and optimization for PCIe and IO-centric workloads.

What we're looking for

Master's or PhD in a relevant discipline such as Computer Science, Electrical Engineering, or Computer Engineering (or equivalent experience).
10 years of relevant work or research experience.
Excellent mathematical and analytical skills.
Work experience demonstrating deep knowledge of computer architecture.
Strong communication, organizational, and interpersonal skills.
Experience with analytical performance modeling, simulation, profiling, and analysis.
Background in data center/cloud computing design with experience crafting hardware for a virtualized environment (preferred).
Expertise in data analysis and visualization; familiarity with GPU computing, parallel programming models, and PCIe/IO-centric workloads (preferred).

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