We are looking for an Engineer to verify the design and implementation of the world’s leading SoC's and GPU's. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. 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 high-speed Serdes platform for the future of computing.
What you'll be doing:
As a key member of our circuit verification team, you will verify the design and implementation of the industry's leading GPU
Responsible for verification of the Mixed Signal CMOS circuit design, architecture, golden models using advanced verification methodologies
You are expected to understand complex mixed-signal CMOS circuits design and implementation, define the verification scope, develop the verification infrastructure and verify the correctness of the design.
Work closely with Multi-functional teams, circuit and logic design, verification, test engineering to accomplish tasks.
What we need to see:
Bachelors Degree in EE, CS or CE or equivalent experience
5+ years of relevant experience or an Advanced Degree with equivalent experience
Experience in deep sub-micron process design experience in CMOS Analog / Mixed Signal Circuit Design
Background with design and verification tools (Cadence's IC design environment, analog circuit simulation tools like HSpice, Finesim, XA)
Experience in crafting test bench environments for component and top level circuit verification
Expertise in System Verilog or similar HVL and strong debugging and analytical skills
Perl and C/C++ programming language experience desirable
Strong communication skills and ability & desire to work as a great teammate are huge plus.
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.
#LI-Hybrid
Skills Required
- Bachelors Degree in EE, CS or CE or equivalent experience
- 5+ years of relevant experience or an Advanced Degree with equivalent experience
- Experience in deep sub-micron process design experience in CMOS Analog / Mixed Signal Circuit Design
- Background with design and verification tools (Cadence's IC design environment, analog circuit simulation tools like HSpice, Finesim, XA)
- Experience in crafting test bench environments for component and top level circuit verification
- Expertise in System Verilog or similar HVL and strong debugging and analytical skills
- Perl and C/C++ programming language experience desirable
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.”
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