Applied Machine Learning Engineer - AI for VLSI Design

Applied Machine Learning Engineer role focused on building AI-driven software systems for VLSI and circuit design in NVIDIA’s Circuit Solutions Group (hybrid in Santa Clara, CA).

Responsibilities

• Collaborate in a multi-functional team across projects for pre-silicon and post-silicon custom circuit design
• Work with data related to Circuit/Layout Optimization and Spice correlation
• Research and implement frontier electronic design automation (EDA) techniques
• Build and improve agentic AI solutions for VLSI design problems
• Analyze problems and datasets, raise and validate hypotheses, and design/build models and algorithms
• Iterate on models/algorithms to achieve the desired QOR

Requirements

• MS in Electrical/Computer Engineering (or equivalent experience) with 3+ years experience
• OR PhD with 1+ years experience in Electrical/Computer Engineering
• Strict requirement: experience in Combinatorial Optimization, Agentic AI and large language models, and Machine Learning for Chip Design & EDA
• Proven ability in Algorithms/Data Structures/Applied Math/Machine Learning and software programming
• Proven ability to write code in Python and C++
• Experience in Applied Math/Machine Learning/Software programming with proven ability to write code in Python and C++

Technologies

• Python
• C++

Benefits

• Eligibility for equity and benefits

Ways to Stand Out

• Prior experience in large-scale EDA software development (plus)
• Prior experience in CMOS layout drawing, including schematic-to-layout translation and DRC/LVS compliance (definite plus)
• Enjoy working across multiple levels and teams across organizations (engineering/research, product, sales and marketing)
• Effective verbal and written communication, plus technical presentation skills
• Self-starter with enthusiasm for continuous learning and sharing findings with the team

Location: Santa Clara, CA (hybrid)

Salary: USD 152,000 - 264,500 per year