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NVIDIA

Designs the chips and software that power AI

Senior DFT Power Methodology Engineer

Hardware Validation & TestingConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • BSEE (or equivalent experience) with 12 or more years, MSEE with 10 or more years, or PhD with 6 or more years of experience in DFT design and power.
  • Understanding of fundamental design-for-test topics and VLSI areas of power, timing, and voltage noise.
  • Knowledge of statistical tools for data analysis and insights.
  • Exposure to multifunctional areas including RTL and clock design, static timing analysis, place-and-route, and power.
  • Experience with silicon debug and bring-up on ATE or SLT platforms.
  • Ability to think like a programmer and translate work into action using AI coding harnesses.

Responsibilities

  • Innovate in DFT Power, Thermal, and Voltage Noise Methodology areas.
  • Work on low-power and thermal solutions for manufacturing tests for datacenter GPUs.
  • Partner with Product Development and Power Architecture teams to implement new methodologies for improving outgoing chip quality.
  • Perform post-silicon power data analysis to architect next-generation solutions.
  • Develop and deploy DFT methodologies for next-generation products using applied machine learning and generative AI solutions.
  • Mentor junior engineers on test designs and trade-offs, including cost and quality.

Desired Qualifications

  • Experience with Power Analysis, Thermal Analysis, and IR Drop tools.
  • Experience applying AI to EDA-related problem-solving.
  • Experience managing DFT Power Methodology for designs.
  • Experience in post-silicon debug for thermal and IR Drop.

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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