Senior ASIC Front End Infrastructure Engineer

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Santa Clara, CAWestford, MAAustin, TXDurham, NC
Salary
$184,000–$287,500 / yr
Posted
51 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $175k
This role $236k
$118k most similar roles pay here $306k

This role pays more than 89% of similar roles. Most pay $144,350–$206,450 — the shaded band above. At the midpoint, this role pays about $236k versus about $175k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior ASIC Front End Infrastructure Engineer

As a Senior ASIC Front End Infrastructure Engineer, you will join the dedicated Infrastructure team to develop and maintain the tooling and environment necessary for DV and RTL Design of leading GPUs. You will be responsible for deploying AI toolsets in secure configurations, utilizing ML, DL, and AI techniques to automate infrastructure tasks and improve design productivity. Your daily work involves improving the speed and extensibility of GPU front end build flows, managing Continuous Integration systems, and overseeing compute farm, filer, and network topology requirements at cloud scale. You will utilize Python, Perl, or other systems programming languages alongside Make-based build systems and Jenkins for pre-submit verification. The role addresses technical challenges in high-performance computing environments, specifically focusing on infrastructure reliability, performance instrumentation, and the automation of complex hardware design workflows.

What you'll do

  • Deploy and manage AI toolsets at scale in secure configurations for hardware design teams.
  • Use ML/DL/AI techniques to automate infrastructure tasks and improve designer productivity.
  • Improve the speed, flexibility, and extensibility of the GPU front-end build flow.
  • Maintain and advance the GPU Continuous Integration system using modern source management methodologies.
  • Manage compute farm, filer, and network topology requirements at cloud scale.
  • Deploy and optimize technologies such as containers, volume cloning, and distributed storage.
  • Forecast hardware design compute resources and EDA needs for executive reporting.
  • Implement tracking metrics to resolve operational issues and improve overall design efficiency.

What we're looking for

  • Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
  • 8+ years of relevant work experience.
  • Proficiency in Python, Perl, or other systems programming languages with a preference for OO design.
  • Experience using AI tools for development and automation.
  • Experience with Make-based build systems in large, distributed computing environments.
  • Experience with Continuous Integration pipelines and pre-submit verification flows, such as Jenkins.
  • Knowledge of the verification domain for complex ASICs or CPUs using random stimulus, functional coverage, and assertion-based methodologies.
  • Strong problem-solving, debugging, and analytical skills to resolve intermittent issues in complex computing environments.

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