Role at a glance
- Salary
- $184K – $356.5K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ years of relevant work experience
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The ASIC Infrastructure Engineer will build and continuously improve the tooling, environments, and infrastructure that support NVIDIA hardware design and verification teams. The role focuses on deploying AI-enabled automation, scaling compute and storage environments, improving GPU build and continuous integration flows, and increasing design productivity.
What You'll Do
- Deploy AI toolsets at scale in secure configurations for 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
- Deploy and continuously improve compute farm technologies such as containers, volume cloning, distributed storage and distributed...
- Deploy tracking metrics to resolve operational issues, drive forecasting, and improve design productivity
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Programming proficiency in Python, Perl, or another systems programming language; experience with AI tools, Make-based build systems, continuous integration pipelines, and verification of complex ASICs or CPUs.
Required
- 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 and/or pre-submit verification flow experience, for example using Jenkins
- Verification domain knowledge with complex ASICs or CPUs using techniques such as random stimulus, functional coverage and...
- Strong problem-solving, debugging and analytical skills
- Good interpersonal skills and ability & desire to work as a great teammate
Preferred
- OO design preferred
Original job description
Content provided by the employer
Original job description
Content provided by 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.
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.
About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.