Applied AI Engineer - VLSI Design

Nvidia

Hybrid

Quick summary

Work type: Hybrid
Location: Santa Clara, CA
Salary: $136,000–$218,500 / yr
Posted: 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 $202k

This role $177k

$123k most similar roles pay here $257k

This role pays less than 63% of similar roles. Most pay $160,000–$244,012 — the shaded band above. At the midpoint, this role pays about $177k versus about $202k 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 855 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 843 roles with salary data.

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At a glance

TL;DR · Applied AI Engineer - VLSI Design

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As a Software Engineer at NVIDIA’s custom RAM design team, you will play a pivotal role in developing AI agents that leverage machine learning models to enhance VLSI design processes. Your day-to-day responsibilities include designing and deploying infrastructure for LLM-powered solutions, fine-tuning these models, and integrating them with CAD flow systems to solve complex engineering challenges. You will collaborate closely with cross-functional teams across different geographies to build innovative agentic AI solutions that improve the efficiency of circuit design. The ideal candidate has a strong background in electrical engineering or computer science, with extensive experience in machine learning, deep learning, and software development using Python. Proficiency in fine-tuning large language models, building multi-agent systems, and working with vector databases is essential, along with solid skills in data structures, algorithms, and software engineering principles.

Skills

Python LLMs RAG pipelines Vector databases CI/CD Large Language Models Agentic frameworks Docker Kubernetes PostgreSQL Git Jenkins

What you'll do

Design and develop AI applications using LLMs and agentic frameworks for VLSI engineering.
Build infrastructure to deploy LLM-powered solutions for engineering assistants and dialogue systems.
Develop agentic AI solutions to solve complex VLSI engineering problems and integrate them with CAD flows.
Fine-tune machine learning models and build advanced multi-agent systems for efficient chip design.
Maintain design databases and dashboards using agentic retrieval mechanisms to expedite circuit design closure.

What we're looking for

Master's or PhD degree in Electrical Engineering, Computer Science, or equivalent experience.
5+ years of industry experience in software development, machine learning, and VLSI design.
Proficiency in Python for rapid prototyping with knowledge of data structures and algorithms.
Experience fine-tuning large language models and building multi-agent systems.
Strong analytical, communication, and interpersonal skills for dynamic team environments.
Familiarity with version control, testing, CI/CD methodologies, and software development standards.

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