AI & Chip Design Intern (Summer 2026)

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What You'll Work On

You will contribute to applied research and engineering projects that sit at the intersection of AI/ML, systems, and chip design. Possible project areas include:

• Building intelligent automation and LLM-based agents that assist chip designers and verification engineers

• Developing evaluation pipelines from large-scale verification data

• Contributing to R&D efforts that apply machine learning to simulation, acceleration, or design-space exploration

• Building Python and cloud-native tooling for verification workflows

• Exploring open-source software, IDE plugins, or developer-productivity tools for chip-design engineers

• Building high-quality user interfaces for human-agent collaboration

Throughout the internship, you'll gain essential engineering skills including research exploration, requirements definition, project planning, coding, debugging, testing, and documentation. You will work closely with a dedicated mentor and present your work at the end of the summer. You will also get to interact with customers.

You will also participate in immersive training on Cadence's core verification technologies and join fun events with other interns.

Requirements

• Currently pursuing a BS or MS Computer Science, Computer Engineering, Electrical Engineering, or a related field

• Strong proficiency in Python

• Solid understanding of data structures, algorithms, and software engineering fundamentals

• Demonstrated research or engineering background in one of the following:

  • AI/ML (fundamental or applied)
  • Chip design or computer architecture
  • Systems and software engineering

• Good communication skills and the ability to work collaboratively

• Interest in developing AI-enabled workflows for chip design or verification

Nice to Have

• Prior experience building LLM-powered agents for complex problems

• Familiarity with chip-design concepts or verification (through coursework or projects)

• Exposure to cloud services, distributed systems, or containerized environments

• Experience at an early-stage startup or in fast-moving research environments

• Experience developing IDE extensions or plugins (e.g., VS Code)

• Strong analytical and problem-solving skills

• Interest in learning both modern EDA technologies and cutting-edge applied AI

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