Applied Machine Learning Engineer - AI for VLSI Design

NVIDIA•Santa Clara, CA

9d•$152,000 - $264,500•Hybrid

About The Position

NVIDIA’s Circuit Solutions Group builds AI-driven software systems for circuit design, combining automation algorithms, deep learning models, and agentic workflows to accelerate end-to-end design automation. The Applied Machine Learning Engineer will work on pre-silicon and post-silicon custom circuit design and related data, circuit and layout optimization, and SPICE correlation. The role involves researching and implementing frontier electronic design automation solutions and developing agentic AI solutions for VLSI design. The engineer will analyze problems and datasets, formulate and validate hypotheses, and design and build models and algorithms until they achieve the desired quality of results (QOR).

Requirements

MS (or equivalent experience) and 3+ years of experience, or a PhD and 1+ years of experience, in Electrical or Computer Engineering.
Experience in combinatorial optimization, agentic AI and large language models, and machine learning for chip design and EDA.
Experience with algorithms, data structures, applied math, machine learning, and software programming, with demonstrated ability to write Python and C++ code.

Nice To Haves

Prior experience in large-scale EDA software development.
Prior experience in CMOS layout drawing, including schematic-to-layout translation and DRC/LVS compliance.
Enjoy working with multiple levels and teams across engineering/research, product, sales, and marketing.
Effective verbal and written communication and technical presentation skills.
Self-starter with a passion for growth, enthusiasm for continuous learning, and willingness to share findings across the team.

Responsibilities

Work within a multifunctional team on projects involving pre-silicon and post-silicon custom circuit design and related data, circuit and layout optimization, and SPICE correlation.
Research and implement frontier solutions in electronic design automation.
Build and innovate agentic AI solutions for VLSI design problems.
Analyze problems and datasets, raise and validate hypotheses, and design and build models and algorithms to achieve the desired QOR.