Applied Machine Learning Engineer, Circuit Design - New College Grad 2026

US, CA, Santa Clara

US, CA, Remote

Full time

JR2011517

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!

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.

What you'll be doing:

• Work within a multi-functional team on projects involving pre-silicon and post-silicon hardware design data, circuit optimization, SPICE correlation, and AI systems for EDA/design automation.

• Work on applications ranging from silicon data analysis, manufacturing process variation analysis, VLSI circuit design, timing, and agent-driven design exploration and agent flow optimization.

• Translate requirements into data science, AI/ML, and agentic system problems; architect and build solutions.

• Test and release models and AI systems that integrate with existing machine learning, design automation, and visualization tools within the organization.

• Analyze datasets, raise and validate hypotheses, extract relevant features, and build models and self-improving workflows on top of them.

• Optimize models, algorithms, and autonomous optimization systems until they reach the desired QOR.

What we need to see:

• Master's or PhD in Electrical or Computer Engineering, Computer Science, or Applied Mathematics (or equivalent experience).

• Knowledge in circuit design, VLSI, ASIC, EDA, silicon analysis, or custom circuit design is required.

• Prior experience in Applied Math/ML/Software programming with proven ability in writing code in Python and C++.

Ways to stand out from the crowd:

• Experience building AI systems for EDA, design automation, or circuit design workflows.

• Research or project experience in AI-driven EDA, circuit optimization, design-space exploration, or autonomous design systems.

• Experience building agentic systems, autonomous optimization loops, self-improving AI systems, or production-scale AI/ML platforms.

• Experience with deep learning algorithms, AI agent frameworks, and tools such as PyTorch, LangChain, or LangGraph is a definite plus.

NV IDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for 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 the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3.

You will also be eligible for equity and benefits ( .

Applications for this job will be accepted at least until May 1, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry.

Learn more about NVIDIA .