NVIDIA

AI computing

AppliedMachineLearningEngineer,CircuitDesignNewCollegeGrad2026

$116–219k Santa Clara, California, United States FULL TIME Remote Friendly
The Brief

“Applied Machine Learning Engineer, Circuit Design - New College Grad 2026 at NVIDIA. Skills: Applied Machine Learning, Circuit Design, AI systems for EDA, Agentic workflows. 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 ag”

What You'll Achieve.

Accelerate end-to-end design automation; Reach the desired QOR (Quality of Results)

Industry & Context.

AI computing
Problems you'll solve

Problem-solving; Hypothesis validation

What They're Looking For.

Must Have

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++

Nice to Have

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

What You'll Do.

Work within a multi-functional team on projects involving pre-silicon and post-silicon hardware design data

and AI systems for EDA/design automation

Work on applications ranging from silicon data analysis

manufacturing process variation analysis

and agent-driven design exploration and agent flow optimization

Translate requirements into data science

and agentic system architect and build solutions

Test and release models and AI systems that integrate with existing machine learning

and visualization tools within the organization

raise and validate hypotheses

extract relevant features

and build models and self-improving workflows on top of them

and autonomous optimization systems until they reach the desired QOR

How You'll Work.

Team & Collaboration

Work within a multi-functional team

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