Senior ASIC Front End Infrastructure Engineer
At a glance
Senior Platform & Infrastructure role at NVIDIA. US, CA, Santa Clara · full-time.
In listing Infrastructure Engineer salary
devopsroles summary, based on the employer's posting.
What you'll do
- Deploy secure AI toolsets for hardware design groups and apply machine-learning methods to automate infrastructure tasks
- Make GPU front-end builds faster and easier to extend, while advancing continuous integration and source management
- Trace difficult flow breakdowns to their root cause and move teams from older workflows to replacements
- Guide cloud-scale compute, storage and network systems, including containers and distributed computing
- Forecast compute and EDA demand, report resource needs, and use tracking measures to improve design productivity
What you bring
- At least eight years in relevant work and a master's in a listed engineering or computing field, or equivalent experience
- Programming skills in Python, Perl or another systems language; object-oriented design is preferred
- You've applied AI tools to development or automation and worked with Make-based builds in distributed environments
- Experience with continuous integration or pre-submit checks, plus verification knowledge involving complex ASICs or CPUs
- You can debug stubborn infrastructure faults and bring strong analysis, problem-solving and teamwork skills
Who this fits
This suits a senior engineer who wants to improve infrastructure for hardware design teams and is willing to investigate rare, difficult failures. The work combines AI automation, GPU build systems, compute resources and ASIC or CPU verification.
From the employer
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.
Applications for this job will be accepted at least until July 27, 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.
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