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NVIDIA

Designs the chips and software that power AI

ASIC Physical Design Engineer New Grad - Netlisting

Silicon & ASIC DesignConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A Master's or PhD degree in Electrical or Computer Engineering, or equivalent experience, is required.
  • Knowledge of logic equivalence checking and formal verification from RTL to tapeout using industry-standard tools is required.
  • Understanding of hardware architecture and hands-on skills in RTL or logic design for timing closure are required.
  • Experience in clock-domain-crossing checking and MTBF analysis using EDA tools such as Synopsys or Cadence, or in-house tools, is required.
  • Background with logic synthesis at block or full-chip level, in project execution or flow development, is required.
  • In-depth knowledge of industry-standard EDA tools in related fields is required.
  • Experience in programming and scripting languages such as Perl, TCL, Make, and Python is required.

Responsibilities

  • Drive physical design of high-frequency, low-power CPUs, GPUs, and SoCs at block, cluster, or full-chip level, focusing on netlist-related work including equivalence checking, asynchronous checking such as clock-domain-crossing checks and MTBF analysis, logic synthesis, and netlist quality checks.
  • Help generate and implement engineering change orders (ECOs).

Desired Qualifications

  • Experience in logic synthesis and equivalence checking or formal verification, with familiarity with industry tools and flows.
  • Hands-on debugging capability and problem-solving skills.
  • Experience improving workflows and productivity through effective use of AI.

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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