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NVIDIA

Designs the chips and software that power AI

Verification Engineer - ARM Fabric Unit Level

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.
  • At least 2 years of demonstrated ability in verification closure of complex units, subsystems, or system-on-chip-level verification.
  • Proven experience in ARM architecture and protocols, including AXI, AHB, and APB.
  • Experience with SystemVerilog and Universal Verification Methodology.
  • Exposure to industry-standard verification tools for simulation and debug.
  • Good interpersonal skills and the ability to collaborate with cross-cultural global teams and work in a matrix organization.

Responsibilities

  • Develop Universal Verification Methodology-based verification test benches and methodologies to verify an in-house ARM architecture-based distributed fabric transporting control, sidebands, and data.
  • Architect test benches and craft the verification environment using SystemVerilog and Universal Verification Methodology.
  • Define test plans, tests, and verification infrastructure for modules, clusters, and systems.
  • Build efficient and reusable bus functional models, monitors, checkers, and scoreboards.
  • Implement functional coverage and coordinate the verification closure process for the unit.
  • Work with architects, designers, FPGA, and post-silicon teams to ensure the unit is robust.

Desired Qualifications

  • Exposure to using AI tools such as Claude or Cursor extensively for code development.
  • A mentality toward constant improvement and building a multiplier effect through work and automation.
  • Exposure to formal verification.

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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