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NVIDIA

Designs the chips and software that power AI

Principal CPU Performance Architect

Silicon & ASIC DesignUpdated on Oct 31
Full-time

About the Job

Requirements

  • Deep understanding of new CPU microarchitecture and architecture.
  • A proven track record of CPU microarchitectural innovation across areas such as Front End CPU Uarch, Midcore CPU Uarch, and Memory Subsystem CPU Uarch.
  • Experience in performance modeling, debugging, and demonstrating the merit of innovative ideas.
  • Ability to collaborate closely with build and verification teams to implement microarchitectural improvements.
  • At least 16 years of experience in a frontline role within new CPU projects.
  • A bachelor's degree in Electrical Engineering, Computer Engineering, or a related field, or equivalent experience.
  • Strong critical thinking, communication, and advocacy abilities.

Responsibilities

  • Innovate and improve CPU performance through modern microarchitectural ideas.
  • Model potential improvements to determine their merit and feasibility.
  • Implement effective solutions and collaborate closely with build, verification, and post-silicon teams.
  • Resolve critical issues related to timing, power, and area to achieve implementation goals.
  • Partner with lead microarchitects to meet the CPU core’s performance, area, and power targets.
  • Advocate for microarchitectural ideas and communicate their benefits and drawbacks in various mediums.
  • Drive the microarchitecture segment and lead by example.

Desired Qualifications

  • Experience leading microarchitecture segments and driving initiatives.
  • A history of collaboration with architects and microarchitects to achieve ambitious targets.
  • Demonstrated ability to think critically and advocate for complex ideas successfully.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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