Senior Asic Front End Infrastructure Engineer

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +3

NVIDIA is seeking experienced ASIC Infrastructure engineers to build and maintain the tooling and environment for GPU design. The role involves deploying AI toolsets, using ML/DL/AI for automation, improving build flows, managing CI systems, and forecasting compute resources. The engineer will focus on infrastructure improvement to enable hardware designers, with an emphasis on automation, scale, and performance.

What you'd actually do

  1. Deploy AI toolsets at scale in secure configurations for use by all HW Design teams
  2. Use ML/DL/AI techniques to automate Infrastructure work and improve Design team productivity
  3. Improve the speed, flexibility and extensibility of the GPU front end build flow
  4. Keep the GPU Continuous Integration system at the cutting edge of source management methodologies
  5. Guide compute farm, filer, and network topology requirements at cloud scale

Skills

Required

  • Python
  • Perl
  • Make based build systems
  • Continuous Integration pipeline experience
  • Verification domain knowledge
  • Problem-solving
  • Debugging
  • Analytical skills

Nice to have

  • OO design
  • AI tools for development and automation
  • Jenkins

What the JD emphasized

  • elite ASIC Infrastructure engineers
  • 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
  • at scale, seamlessly transitioning teams from old flows
  • 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
  • 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
  • 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