Senior ASIC Front End Infrastructure Engineer

Reposted 23 Hours Ago
5 Locations
In-Office or Remote
184K-357K
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design and deploy machine learning techniques to enhance infrastructure efficiency, improve GPU build flow, and ensure peak performance of hardware design environments.
Summary Generated by Built In

NVIDIA is seeking elite ASIC RTL/Verification ASIC engineers to develop the core Verification and RTL infrastructure of the world's leading GPUs. This position offers the opportunity to have a real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to artificial intelligence to 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? Learning and deploying best in class internal and industry solutions? 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:

  • Define and deploy ML/AI techniques to improve Infrastructure efficiency and support

  • Improve the speed, flexibility and extensibility of the GPU front end build flow

  • Keep the GPU Continuous Integration system at the cutting edge of industry techniques

  • Guide compute farm, filer, and network topology requirements

  • Deploy new compute farm technologies such as containers, volume cloning, distributed storage and distributed compute at scale

  • 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 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.

#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 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.

Applications for this job will be accepted at least until October 4, 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

Jenkins
Make
Perl
Python
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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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