This role pays less than
79%
of similar roles. Most pay
$152,875–$235,750
— the shaded band above.
At the midpoint, this role pays about
$150k
versus about
$194k
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
1150 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 912 roles with salary data.
Applied Machine Learning Engineer, AI for VLSI Design - New College Grad 2026 will join the Circuit Solutions Group to develop AI-driven software systems for circuit design. This role involves building and innovating agentic AI solutions for VLSI design problems while researching frontier electronic design automation techniques. Day-to-day responsibilities include working within a multi-functional team on projects involving pre-silicon and post-silicon custom circuit design, layout optimization, and spice correlation. The candidate will analyze datasets, validate hypotheses, and build models and algorithms to reach desired quality of results. Required expertise includes combinatorial optimization, agentic AI, large language models, machine learning for chip design, and EDA backgrounds. Technical skills required include proficiency in Python, C++, and core knowledge of data structures and algorithms. The work focuses on automating end-to-end circuit design through automation algorithms and deep learning models.
What does a Machine Learning Engineer earn in California?
Median $232000 from 183 postings across 28 companies.
Python
C++
Machine Learning
Large Language Models
Agentic AI
EDA
VLSI Design
Combinatorial Optimization
Circuit Design
Layout Optimization
Spice Correlation
Data Structures
Algorithms
Applied Math
CMOS Layout
DRC
LVS