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NVIDIA

Designs the chips and software that power AI

ASIC Verification Engineer New Grad - Memory Management

Full-TimeUpdated
$100k - $189.8k+ Equity
Entry
Bachelor's, Master's
Madison, AL, USA+2 moreMore locations: Durham, NC, USA | Hillsboro, OR, USA
In Person
Hardware EngineeringHardware Validation & Testing
Company Historically Provides H1B Sponsorship

About the job

Requirements
  • Pursuing or recently completed a Bachelor of Science or Master of Science in Electrical Engineering, Computer Science, Computer Engineering, or a related field, or equivalent experience.
  • Exposure to computer architecture, ASIC design, and verification methodology is required.
  • Strong proficiency with SystemVerilog, C and/or C++, test planning, coverage closure, and creating reusable verification components.
  • Knowledge of constrained-random testing with functional coverage and assertion-based verification.
  • Understanding of object-oriented programming concepts.
  • Exposure to simulation tools such as VCS and IES, and debug tools such as Debussy and GDB.
  • Good debugging and problem-solving skills.
Responsibilities
  • Understand the design and implementation, with a focus on the Memory Management Unit; define verification scope; develop verification infrastructure including testbenches, Bus Functional Models (BFMs), checkers, and monitors; implement test and coverage plans; and verify design correctness.
  • Collaborate with architects, designers, and software engineers across sites to accomplish goals.
  • Plan and work on the strategic direction of the testbench methodology.
Desired Qualifications
  • Understanding of memory subsystem microarchitecture, cache topologies and policies, memory management, interconnects, and/or arbiter designs.
  • Exposure to Universal Verification Methodology (UVM), SystemVerilog checkers and scoreboards, assertion-based verification, and Semiformal Verification (SFV).
  • Knowledge of Perl or Python.

About the company

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, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
  • Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
  • Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.

What critics are saying

  • Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
  • Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
  • Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.

What makes NVIDIA unique

  • Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
  • The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
  • People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.

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Benefits

  • Company Equity
  • 401(k) Company Match

Growth & Insights and Company News

6 month growth

1%

1 year growth

0%

2 year growth

-1%
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