Full-Time

Principal System Architect

Gpu

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$272k - $431.3k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Remote in USA + 3 more

More locations: Redmond, WA, USA | Santa Clara, CA, USA | Hillsboro, OR, USA

Remote

Remote option available; US work authorization required.

Category
Hardware Engineering (1)

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Requirements
  • Over 15 years in SoC architecture development or similar technical leadership roles
  • Proficiency in evaluating power/performance and architectural modeling in high-level programming languages
  • Strong understanding of SoC system fundamentals, including memory hierarchy, coherency, clocking, power domains, boot and reset, test, and debug methodologies
  • Hands-on experience with silicon bring-up, debug and tuning
  • Excellent interpersonal, leadership, and collaboration skills, with the ability to influence across organizations
  • Outstanding documentation, written, and verbal communication skills
  • Master's degree (or equivalent experience) in Computer Science, Electrical Engineering or Computer Engineering
Responsibilities
  • Define and drive architecture for complex, high-volume GPU products, ensuring they meet ambitious performance and scalability goals
  • Perform and guide power and performance evaluation, trade-off assessments, and architectural modeling to identify optimal chip, package and system construction
  • Lead improvements in architecture, methodology and tools to improve the scalability of our system, collaborating closely with cross-functional engineering teams
  • Specify and optimize SoC subsystems such as memory architecture, test infrastructure and power management
  • Collaborate with RTL, verification, physical design, firmware, and software teams to successfully implement and integrate system components
  • Produce high-quality technical documentation of SoC architecture, specifications, and development trade-offs
  • Provide technical leadership and mentorship to junior architects and engineers, encouraging a culture of excellence and innovation
Desired Qualifications
  • Experience with GPU or AI accelerator architecture, including platform aspects, off-chip I/O technologies, and networked multi-GPU systems
  • Knowledgeable in modern packaging technologies, and their costs and benefits
  • Knowledgeable in AI workload characteristics
  • Outstanding analytical and problem-solving skills with a focus on optimizing performance, power, area, and complexity

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • Rubin delivers 5x faster inference and 3.5x faster training than Blackwell starting H2 2026.
  • Major hyperscalers Microsoft, AWS, Google Cloud, and CoreWe confirmed Vera Rubin implementation ahead of Q3 2026.
  • Rubin Ultra targets 15 ExaFLOPS FP4 inference with 1.5 PB/s NVLink bandwidth per rack in 2027.

What critics are saying

  • HBM4 scarcity from SK Hynix and Micron forces Rubin production cut to 1.5M units in 2026.
  • Kyber NVL144 rack delayed to 2028 due to TSMC 78-layer PCB yield failure, breaking annual cadence.
  • Rubin Ultra cuts HBM4E stacks to 12-Hi, delivering only 2.66x instead of 4x performance gain.

What makes NVIDIA unique

  • Vera Rubin is a six-chip extreme codesigned AI supercomputer platform, not just a GPU.
  • NVIDIA shifted to annual architecture cadence with Rubin, Ultra, and Feynman releases through 2028.
  • Vera CPU with 88 ARM cores enables per-GPU efficiency and 1/10 Blackwell operational costs.

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Benefits

Company Equity

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Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-2%

2 year growth

-3%
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