[2027 Internship] CPV AI Integration Engineer Intern

Job Description

MediaTek’s CPV team is responsible for ensuring the physical design quality of integrated circuit layouts for our chips. We have unique career opportunities for students interested in applying AI and software skills towards improving chip verification workflows through cutting-edge technologies. We are looking for those with talent and ambition to explore how emerging AI—including Agentic AI, Large Language Models (LLMs), and AI-powered automation—can innovate and streamline our verification processes.

Students who are eager to work with AI technologies and semiconductor design are a perfect fit for our team. Students will participate in AI research and exploration focused on adopting and integrating AI tools and systems within the Physical Verification domain. This role offers hands‑on experience with modern AI frameworks, LLM APIs, and agent‑based systems, plus the opportunity to contribute to meaningful projects that directly improve team productivity and efficiency.

What you will do

Explore and evaluate emerging AI technologies relevant to CPV workflows

Design and prototype AI-powered solutions to automate repetitive CPV tasks (log analysis, DRC, scripting, report generation)

Experiment with prompt engineering and agent orchestration to optimize AI workflows

Integrate third‑party AI tools and APIs into existing CPV infrastructure

Develop proof‑of‑concept applications demonstrating AI‑driven productivity improvements

Analyze and measure the impact of AI solutions on team workflows

Collaborate with CPV engineers to identify pain points where AI can add value

Document findings and create adoption guidelines for AI technologies within the team

Stay current with AI trends and assess new tools for potential integration

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Main Requirements and Qualifications

[What you will bring]

- Currently enrolled in your BSc/MSc from reputable university

- Proficiency in Python and hands‑on experience with scripting/automation

- Basic understanding of AI/ML concepts and how modern LLMs and agent systems work

- Experience with at least one LLM API (OpenAI, Anthropic, Google) or equivalent

- Good communication skills, self‑motivated and well‑organized

- Eagerness to learn and adapt to new tools and technologies

- Curiosity about emerging AI trends and emerging technologies

- Knowledge of chip design, physical verification, or semiconductor EDA tools is a plus

- Experience with prompt engineering, RAG, or AI agent frameworks (LangChain, CrewAI, Dify) is a plus

- Familiarity with cloud AI services (GCP, AWS, Azure) is a plus

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