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# Senior ASIC Front End Infrastructure Engineer

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Programming, Computer Engineering, Continuous Integration, Software Debugging, Microprocessors, Distributed Data Store, Distributed Systems, Perl (Programming Language), Network Topologies, Python (Programming Language), Object-Oriented Software Development, Software Tools, System Programming, Application Specific Integrated Circuits, Information Technology, Build Tools, Jenkins
- **Published:** May 28, 2026
- **Apply:** https://www.juju.com/job/00000000g39vqk

## About the Role

+ 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

+ 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


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