ASIC Clocks Verification Engineer - New College Grad 2026

Posted Yesterday
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Santa Clara, CA, USA
Hybrid
116K-190K Annually
Entry level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Verify high-frequency GPU clock structures, collaborate with architecture, design, floor-planning, software, timing, and DFT teams, and debug silicon issues. Develop verification approaches using SystemVerilog and UVM, improve team productivity with Perl or Python, address sub-micron clocking challenges, and propose design-efficiency improvements. Requires a master’s degree in electrical engineering or equivalent experience, plus experience in design verification, logic design, and logic synthesis.
Summary Generated by Built In

NVIDIA has continuously reinvented itself over two decades. Our 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. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can take on, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today.

The GPU clocks group is looking for an exceptional ASIC Clocks Verification Engineer. The team is responsible for crafting all aspects of GPU clocking. The team collaborates with the front design team to understand the clocking requirements for the chip. The clocks team interacts with the floor-planning and back-end team to help craft the physical floorplan of the chip. The team explains the programming model to the SW team to come up with an efficient clock programming sequence. The team works with the silicon solution team to triage silicon or programming bugs in the lab.

What you'll be doing:

  • As a Clocks team member, you will be collaborating with other architects, ASIC designers and verification engineers to verify high frequency clock structures.

  • Be able to engage with multiple teams and design the GPU clock structure to satisfy all the architectural constraints.

  • Your understanding of general verification principles will be valuable to verify the clocks design.

  • Together with other team members, we deliver clock information to SOC verification team, timing and DFT teams. You will use Perl to improve the productivity of the above teams.

  • Collaborate with Software and product group to debug GPU clock silicon bugs in our new products.

  • Understand and design clocking structures to overcome sub-micron design challenges.

  • You will also identify improvements in the current design and propose and implement new ways to improve the efficiency in the GPU clocking design.

What we need to see:

  • A Master’s degree in Electrical Engineering (or equivalent experience).

  • Practical experience with SystemVerilog and Universal Verification Method (UVM).

  • Experience with Design Verification, Logic Design, and Logic Synthesis.

  • Strong coding skills in Python, Perl, or other industry-standard scripting languages.

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. Are you creative and autonomous? 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 116,000 USD - 189,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 13, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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

  • Master's degree in Electrical Engineering or equivalent experience
  • Practical experience with SystemVerilog
  • Practical experience with Universal Verification Methodology (UVM)
  • Experience with design verification
  • Experience with logic design
  • Experience with logic synthesis
  • Strong coding skills in Python, Perl, or other industry-standard scripting languages

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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