The NVIDIA GPU clocks group is looking for an excellent Senior ASIC Design Engineer to join the team. The Team is responsible for crafting all aspects of GPU clocking. We collaborate with the frontend design team to understand the clocking requirements for the chip, and work with backend teams to understand the physical restrictions. The GPU clocks group architects, designs and validates the clocks RTL. The complexity of clocks RTL has increased many fold to support our features that power our product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence.
What you’ll be doing:
As a Clocks team member, you will collaborate with other architects, ASIC designers and verification engineers to design high frequency and low power clocks. You should be able to engage with multiple teams and design the GPU clocks to satisfy all the architectural constraints. You will need to run and enhance some in-house flow to guarantee the good quality of clocks RTL and netlist, drive the issues to close. Together with other team members, we deliver clock information to SOC verification team, timing and DFT teams. You will use Perl/Python to improve the productivity of the above teams. Collaborate with software and silicon solution team to debug GPU clock silicon bugs in our new products.
What we need to see:
BS or (MS preferred) in EE or equivalent experience. 2+ years of meaningful work experience.
Your ability to thrive in a dynamically changing environment.
Validated experience in RTL design (Verilog), verification and logic synthesis. Your strong coding skills in Perl or Python or other industry-standard scripting languages.
Deep understanding of sub-micron silicon issues like noise, cross-talk, and OCV effects is a plus. Good understanding of backend flows and requirements is a plus.
DFT knowledge is a plus. Experience in implementing on-chip clocking networks is desirable.
Excellent analytical and problem-solving skills. Fluent English (both written and spoken) and excellent communication skills.
Good team work spirit, easy to cooperate with team members.
Skills Required
- BS in Electrical Engineering or equivalent experience
- MS in Electrical Engineering
- 2+ years of relevant work experience
- Validated experience in RTL design (Verilog), verification and logic synthesis
- Strong scripting skills in Perl or Python or other industry-standard scripting languages
- Deep understanding of sub-micron silicon issues (noise, cross-talk, OCV effects)
- Understanding of backend flows and requirements
- DFT knowledge
- Experience implementing on-chip clocking networks
- Excellent analytical and problem-solving skills; fluent English and strong communication
- Good teamwork and collaboration skills
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.
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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.
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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.
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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
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.”
