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# AI Hardware Architect

- **Company:** NVIDIA Ltd.
- **Location:** Monte Sereno, CA, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Engineering, Firmware, Network Protocols, Systems Architecture, Graphics Processing Unit (GPU), Large Language Models, Hardware Acceleration
- **Published:** October 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ai-hardware-architect-austin-tx--00857153-ba49-426e-a9f5-9e89f434de22

## About the Role

Hardware Architecture, Artificial Intelligence (AI), Computer Architecture, Hardware Architecture, Artificial Intelligence (AI), Architectural Analysis, GPU (Graphics Processing Unit), CPU (Central Processing Unit), Power Management, Network Protocols, * Master's Degree in Computer Engineering or Electrical Engineering (or equivalent experience)

 * 8+ years of relevant industry experience.
 * Experience building high performance microarchitectural structures. Experience with industry standard bus protocols.
 * Clear understanding of the performance,powerand security implications of microarchitectural features.
 * Strong interpersonal,communicationand teamwork skills.
 * A drive to continuously learn and expand architectural breadth and depth.
 * Excellent coding and algorithmic thinking skills. Good understanding of LLMs.
 * Publications or other evidence of original chip/system architecture work is a plus.

## Description

* Work on groundbreaking GPU and CPU systems. Understand them across a range of disciplines andidentifyareas for improvement.
 * Study the applications and models running on Nvidia hardware and their architectural implications
 * Come up withmicroarchitectural solutions for connectivity, coherency, power management, security, memorymanagementand other SOC level issues.
 * Understand and help driveimplementationof bus protocols, networking protocols, memoryaccessand security solutions across a range of products.
 * Work with software, firmware,platformand multi-functional teams on system architecture.
 * Model, analyze, and explain the performance and power advantages of Nvidia solutions.
 * Guide customers and firmware engineers to extract the most performance from microarchitectural structures.