Senior ASIC Design Verification Infrastructure and Tools Engineer – GPU

Reposted 18 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
136K-265K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Drive efficiency in High-Speed IO engineering through automation, improve verification flows, collaborate with engineers, and enhance productivity metrics.
Summary Generated by Built In

NVIDIA is seeking outstanding Senior Design Verification Engineers with a specialty in tools and automation to drive efficiency and collaboration among our High Speed IO engineering teams.  This position offers the opportunity to have a big impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to artificial intelligence to self-driving cars and supercomputers.

Our DV infrastructure and methodology team automates, analyzes, and optimizes the verification and deployment of next-generation hardware and firmware designs throughout Nvidia.

What you’ll be doing:

  • Improve the speed, flexibility, and extensibility of the High-Speed IO front end integration, build, and verification flows

  • Apply best in class internal and industry tools to enable flows that simplify work processes

  • Find out needs of the team and create solutions; explain to the team how to maximize productivity with the tools you provide

  • Keep the High-Speed IO Continuous Integration system at the cutting edge of industry techniques

  • Collaborate with architects, designers, verification engineers, as well as methodology and infrastructure engineers to accomplish your tasks

  • Deploy tracking metrics to resolve operational issues, drive forecasting, and improve design productivity

  • Remove inefficiency wherever you can find it!

What we need to see:

  • Bachelors or Masters in Computer Science, Computer Engineering, Electrical Engineering or closely related degree (or equivalent experience)

  • 5+ years of relevant industry experience

  • Exposure to computer architecture, ASIC design, and verification methodology is required

  • Experience with verification methodology (UVM or similar)

  • Exposure to design and verification tools (VCS or equivalent simulation tools, debug tools like Verdi interactive, Debussy, GDB)

  • Programming proficiency in Python, Perl, or other Systems Programming language

  • Fluency in Object Oriented Programming with SystemVerilog

  • Experience with Make based build systems in large, distributed computing environments

  • Experience with Continuous Integration pipelines

  • You should display a tenacity to root cause and fix Infrastructure problems, especially intermittent, hard to isolate issues in a complex computing environment

Ways to stand out from the crowd:

  • Experience delivering IP to multiple GPUs/SoCs in parallel

  • Experience creating shareable and maintainable Continuous Integration pipelines in Jenkins

  • Strong verification mindset and intuition

  • Experience applying AI to solve problems or implementing agentic AI flows

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working with us. Are you creative and autonomous? Do you love the challenge of crafting the highest performance & lowest power silicon possible? If so, we want to hear from you. Come, join our GPU ASIC team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field!

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 26, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Skills Required

  • Bachelors or Masters in Computer Science, Computer Engineering, Electrical Engineering or equivalent
  • 5+ years of relevant industry experience
  • Exposure to computer architecture, ASIC design, and verification methodology
  • Experience with verification methodology (UVM or similar)
  • Fluency in Object Oriented Programming with SystemVerilog
  • Programming proficiency in Python, Perl, or other Systems Programming language
  • Experience with Continuous Integration pipelines
  • Experience with Make based build systems in large, distributed computing environments

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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