Applied AI Engineer, VLSI Design

Nvidia

Confirmed live 2 days ago High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Santa Clara, CA
Salary: $136,000–$218,500 / yr
Posted: 25 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $192k

This role $177k

$125k most similar roles pay here $241k

This role pays less than 55% of similar roles. Most pay $162,000–$223,000 — the shaded band above. At the midpoint, this role pays about $177k versus about $192k 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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At a glance

TL;DR · Applied AI Engineer, VLSI Design

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The Applied AI Engineer - VLSI Design joins the custom RAM design team to develop and deploy AI agents that solve complex problems in VLSI design. This role involves building infrastructure for LLM-powered engineering assistants, multi-turn multi-modal dialogue systems, and agentic AI solutions integrated with CAD flow systems. The engineer will also build and maintain design databases and dashboards using agentic and deterministic retrieval mechanisms to expedite circuit design closure. Key responsibilities include fine-tuning large language models and developing RAG pipelines and vector databases. Required skills include proficiency in Python, data structures, algorithms, and software engineering principles like version control and CI/CD. The role focuses on the intersection of innovative circuit design and scalable CAD infrastructure to improve the efficiency and quality of memory technology for AI and accelerated computing.

Skills

Python LLMs Machine Learning Deep Learning Agentic Frameworks RAG Vector Databases VLSI Design CI/CD Version Control Data Structures Algorithms Circuit Design

What you'll do

Design, develop, and deploy AI applications using LLMs and agentic frameworks.
Build infrastructure for LLM-powered engineering assistants and multi-modal dialogue systems.
Develop agentic AI solutions to solve complex VLSI engineering problems.
Fine-tune and integrate machine learning models into existing CAD flow systems.
Build and maintain design databases and dashboards using retrieval mechanisms to fetch engineering data.
Automate circuit design closure processes through the integration of intelligent software tools.

What we're looking for

Master's or PhD degree in Electrical Engineering, Computer Science/Engineering, or equivalent experience.
5+ years of proven industry experience in a related field.
Proficiency in rapid prototyping using Python with strong knowledge of data structures and algorithms.
Experience fine-tuning large language models (LLMs) and building advanced multi-agent systems.
Experience developing RAG pipelines and working with vector databases.
Strong analytical, communication, and interpersonal skills to work in distributed teams.
Proficiency in software development methodologies including version control, testing, and CI/CD.
Prior experience with circuit design or hardware design is a plus.

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