> Markdown version of [/jobs/ext/4163120-ai-hardware-architect](https://www.wearedevelopers.com/jobs/ext/4163120-ai-hardware-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Hardware Architect - **Company:** NVIDIA Corporation - **Location:** United States - **Experience:** Expert - **Salary:** $184,000.0 - $287,500.0 - **Contract:** Permanent contract - **Skills:** Computer Engineering, Memory Management, Firmware, Network Protocols, Systems Architecture, Large Language Models - **Published:** October 18, 2026 - **Apply:** https://startup.jobs/ai-hardware-architect-2100-nvidia-usa-8741488 ## About the Role * 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, power and security implications of microarchitectural features. * Strong interpersonal, communication and 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 and identify areas for improvement. * Study the applications and models running on Nvidia hardware and their architectural implications * Come up with microarchitectural solutions for connectivity, coherency, power management, security, memory management and other SOC level issues. * Understand and help drive implementation of bus protocols, networking protocols, memory access and security solutions across a range of products. * Work with software, firmware, platform and 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.