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# Senior ASIC Front End Infrastructure Engineer

- **Company:** NVIDIA Ltd.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $356,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cyber Security, Computer Programming, Computer Engineering, Continuous Integration, Software Debugging, Microprocessors, Distributed Data Store, Distributed Systems, Perl (Programming Language), Formal Verification, Network Topologies, Python (Programming Language), Object-Oriented Software Development, Systems Development Life Cycle, Software Tools, System Programming, Application Specific Integrated Circuits, Information Technology, Build Tools, Jenkins
- **Published:** May 27, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=07bee54ae3ea142f

## About the Role

Do you have experience in Verification (System development task)?, Do you have a Master's degree?, * 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

## Description

* 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!


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