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NVIDIA

Designs the chips and software that power AI

Verification Engineer - Networking IPs

Hardware Validation & TestingConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • A BTech or MTech in ECE, EE, CSE, or an equivalent degree is required.
  • Over 3 years of experience in verification closure of complex units, sub-systems, or system-on-chip level verification.
  • Proven experience in networking-specific datapath and switching verification intellectual property.
  • Good debugging and analytical skills, with exposure to industry-standard verification tools for simulation and debug.
  • Ability to collaborate with cross-cultural global teams and work in a matrix organization.

Responsibilities

  • Develop verification components and application programming interfaces for unit- and cluster-level test benches to verify queuing and scheduling algorithms and designs.
  • Architect test benches and create verification environments using Specman language and methodology.
  • Define test plans, tests, and verification infrastructure for clusters and systems.
  • Build efficient and reusable bus functional models, monitors, checkers, and scoreboards.
  • Implement functional coverage and own unit- and cluster-level verification closure.
  • Work with architects, designers, FPGA, and post-silicon teams to ensure the unit is robust.

Desired Qualifications

  • Experience with the latest verification methodologies, such as SystemVerilog and Universal Verification Methodology, would be beneficial.
  • Extensive use of AI tools such as Claude or Cursor for code development is a plus.
  • Exposure to formal verification would be beneficial.

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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