NVIDIA is seeking elite ASIC Infrastructure engineers to deliver the tooling and environment that enables DV and RTL Design for the world's leading GPUs. This position offers the opportunity to have a real impact on a dynamic, technology-focused company impacting product lines ranging from consumer graphics to artificial intelligence, self-driving cars, and supercomputers.
Our team of dedicated Infrastructure engineers continuously upgrades the NVIDIA Hardware design environment. We focus relentlessly on Infrastructure improvement so that HW designers can focus relentlessly on their jobs, with Infrastructure that “just works” at worldwide scale and peak performance. Do you like root causing a flow failure, even if it’s rare and hard to reproduce, and others have given up? Rapidly learning and deploying best in class internal and industry solutions including AI harnesses in secure environments that you then use to build Skills and Agents for Infrastructure Automation? Instrumenting flows to measure performance and then improving efficiency? Can you do that at scale, seamlessly transitioning teams from old flows? Then join us!
What you'll be doing:
Deploy AI toolsets at scale in secure configurations for use by all HW Design teams
Use ML/DL/AI techniques to automate Infrastructure work and improve Design team productivity
Improve the speed, flexibility and extensibility of the GPU front end build flow
Keep the GPU Continuous Integration system at the cutting edge of source management methodologies
Guide compute farm, filer, and network topology requirements at cloud scale
Deploy and continuously improve compute farm technologies such as containers, volume cloning, distributed storage and distributed compute at cloud scale
Forecast HW Design compute resource and EDA needs, with reporting up to the CFO’s office
Deploy tracking metrics to resolve operational issues, drive forecasting, and improve design productivity
Deploy information security methods for HW design
Remove inefficiency wherever you can find it!
What we need to see:
Masters Degree in Electrical Engineering, Computer Engineering, Computer Science or related or equivalent experience
8+ years of relevant work experience
Programming proficiency in Python, Perl, or other Systems Programming language. OO design preferred.
Experience using AI tools for development and automation
Experience with Make based build systems in large, distributed computing environments
Continuous Integration pipeline and/or pre-submit verification flow experience, for example using Jenkins
You should display a tenacity to root cause and fix Infrastructure problems, especially intermittent, hard to isolate issues in a complex computing environment
Verification domain knowledge with complex ASICs or CPUs using techniques such as random stimulus, functional coverage and assertion-based verification methodologies
Strong problem-solving, debugging and analytical skills
Good interpersonal skills and ability & desire to work as a great teammate
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 for us. Are you creative and autonomous? Do you love the challenge of crafting the most sophisticated chips in the world? If so, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
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
- Masters Degree in Electrical Engineering, Computer Engineering, Computer Science or related
- 8+ years of relevant work experience
- Programming proficiency in Python, Perl, or other Systems Programming language
- Experience using AI tools for development and automation
- Experience with Make based build systems in large, distributed computing environments
- Continuous Integration pipeline experience, using Jenkins
- Verification domain knowledge with complex ASICs or CPUs
- Strong problem-solving, debugging and analytical 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.”
