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NVIDIA

Applied Machine Learning Engineer, AI for VLSI Design - New College Grad 2026

Reposted 14 Hours Ago
Hybrid
Santa Clara, CA
116K-230K Annually
Entry level
Hybrid
Santa Clara, CA
116K-230K Annually
Entry level
Develop AI-driven software systems for VLSI and circuit design, including machine learning models, combinatorial optimization algorithms, and agentic AI workflows. Analyze datasets, validate hypotheses, and build algorithms for circuit and layout optimization, pre- and post-silicon design, and SPICE correlation. Collaborate across engineering and research teams while advancing electronic design automation solutions.
The summary above was generated by AI

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.


Our team builds AI-driven software systems for Circuit Design: combining automation algorithms, DL models and agentic workflows to accelerate end-to-end design automation. Come join this integral team in our Circuit Solutions Group!


What you'll be doing:

  • Work within a multi-functional team on various projects involving Pre-silicon and Post Silicon custom circuit design and related data, Circuit/Layout Optimization and Spice correlation.
  • Research and implement techniques on frontier solutions of electronic design automation.
  • Build and innovate agentic AI solution for VLSI design problem.
  • Responsible for analyzing the problem or datasets, raise and validate hypotheses, design and build models and algorithm until they reach the desired QOR.

What we need to see:

  • MS or PhD in Electrical/Computer Engineering degree (or equivalent experience).
  • Experience in the following fields is a strict requirement for this role: Combinatorial Optimization, Agentic AI and large language models, Machine Learning for Chip Design & EDA
  • Background in Algorithms/Data Structures.
  • Experience in Applied Math/Machine Learning/Software programming with shown ability in writing code in Python, C++.

Ways to stand out from the crowd:

  • Prior background in large-scale EDA software development is a plus.
  • Prior experience in CMOS layout drawing, including schematic-to-layout translation and DRC/LVS compliance, is a definite plus.
  • Enjoy working with multiple levels and teams across organizations (engineering/research, product, sales and marketing teams).
  • Effective verbal/written communication, and technical presentation skills.

NVIDIA is a pioneer in bringing groundbreaking technology to new markets. We have some of the most forward-thinking and hardworking people in the world working with us. If you're creative and autonomous, we want to hear from you!


#LI-Hybrid

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
116,000 USD – 184,000 USD for Level 2; and 152,000 USD – 230,000 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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