Senior Applied AI and AI Infrastructure Engineer - Chip Design and DFX

Nvidia

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $200,000–$322,000 / yr
Posted: 4 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $216k

This role $261k

$167k most similar roles pay here $339k

This role pays more than 85% of similar roles. Most pay $184,900–$246,150 — the shaded band above. At the midpoint, this role pays about $261k versus about $216k 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 985 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 971 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Applied AI and AI Infrastructure Engineer - Chip Design and DFX

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As a senior member of NVIDIA’s Design-for-X Engineering team, you will lead Applied AI projects involving machine learning and generative AI to solve complex challenges in chip design and manufacturing testing. Your day-to-day responsibilities include managing deployment cycles for AI infrastructure across the organization, serving as a liaison between on-prem infrastructure teams and software developers, and ensuring robust performance through automation and code pipeline maintenance. You will also mentor junior engineers and develop methodologies using Gen AI solutions for next-generation products. The role requires extensive experience in AI infrastructure management, applied machine learning, and generative AI, along with strong programming skills in Python and C++. Additionally, you should have hands-on experience with cloud platforms and data modeling tools like SQL and ETL, as well as the ability to lead large-scale mission-critical Gen AI workloads.

Skills

AWS Azure GCP Python C++ SQL ETL Kubernetes Terraform CI/CD Prometheus PostgreSQL Docker Git AI ML Gen AI Data Modeling Algorithm Design

What you'll do

Develop and manage deployment cycles for AI infrastructure across the organization.
Serve as a liaison between on-prem infrastructure teams and software development teams.
Apply machine learning and generative AI to solve complex problems in Design For Test (DFT).
Mentor junior engineers on test design methodologies and trade-offs.
Help develop DFT methodologies using generative AI solutions for next-generation products.

What we're looking for

At least 10 years of experience in AI Infrastructure management and Applied Machine Learning (MSEE required).
Expertise in building agents and multi-agentic ecosystems with hands-on cloud platform experience.
Proficient in SQL, ETL, data modeling, Python, and C++ programming.
Ability to architect and optimize globally distributed systems for high availability and performance.
Experience applying AI solutions to complex chip design and manufacturing challenges.
Strong mentorship skills and collaborative abilities within a dynamic environment.

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