Senior ASIC Verification Engineer - GPU

Reposted 2 Days Ago
Be an Early Applicant
4 Locations
In-Office or Remote
168K-311K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
As a Senior ASIC Verification Engineer, you will verify GPU hardware through unit level testbench work, collaborate with teams, and support validation activities.
Summary Generated by Built In

NVIDIA is seeking best-in-class ASIC Verification Engineers to verify the world’s leading GPUs. In this role, you will be doing unit level verification of the process scheduling and system interface hardware of the GPU. This position will be working across many NVIDIA teams from software, to architecture, design, methodology, and more. The GPU is used in applications from consumer graphics, through self-driving cars, to artificial intelligence, all of which you will be involved in and learn about. We have crafted a team of extraordinary people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the methodology for verifying the future of computing.

What you’ll be doing:

  • Work on a unit level testbench, working on directed and random tests and test infrastructure, and contributing to the future direction of the methodology for the testbench

  • Partner closely with RTL and architecture teams to help refine the microarchitecture plans to ensure that changes to the design are verifiable

  • Architect and plan the verification strategy and execution for sub-system features impacting your unit

  • Support post-silicon validation activities

  • Harness cutting-edge AI to accelerate testbench development, task automation, debugging and problem-solving in a paradigm-shifting way

What we need to see:

  • BS or MS in electrical engineering or computer engineering or similar area (or equivalent experience)

  • 8+ years of verification experience

  • Exposure to Computer Architecture, ASIC design and verification methodology is required

  • Strong ability with SystemVerilog, test planning, coverage closure, and test bench design

  • Understanding of object oriented programming concepts

  • Strong communication skills.

  • Ability and desire to work as a great teammate

  • Good debugging and problem solving skills

Ways to stand out from the crowd:

  • Experience with assertion-based verification, Semiformal Verification (SFV), Unified Verification Methodology (UVM), SystemVerilog checkers and scoreboards.

  • Perl or Python knowledge

  • Experience with multiple verification methodologies

  • Leadership experience

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Do you want to work at the boundary of software, hardware, and forefront of technology? Would you love the challenge of creating the highest performance chips in the industry? If so, we want to hear from you

#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 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 13, 2025.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.

Top Skills

Perl
Python
Systemverilog
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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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