AI Intern

Description
Advantest America, a global leader in Semiconductor Test and Measurement, is seeking a motivated and innovative engineering student to explore cutting-edge applications of machine learning and generative AI. This internship provides hands-on experience working with emerging
AI systems and integrating them into Advantest’s advanced testing
platforms.

 

Location: Austin, TX or San Jose, CA (headquarters)

 

Role Overview
In this role, you will contribute to research and prototyping efforts focused on LLM-powered reasoning and evaluation systems. You will explore how retrieval-augmented generation (RAG) and agentic workflows can be used to analyze, compare, and assess complex technical content at scale. The internship emphasizes building AI systems that support decision-making, qualitative judgment, and structured feedback in real-world engineering and research environments.

You will work with unstructured and semi-structured documents, design multi-step reasoning pipelines, and evaluate system behavior against domain-specific expectations and constraints.

 

 

Key Responsibilities

 

• Develop and execute an approach for a detailed market analysis in different area of the AI tools and companies

•  

  Competitive analysis of AI usage in the semiconductor market

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  Provide summaries, presentations and guidance about collaborations and partnerships

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  Analyze Project Management execution pipeline and propose efficiency improvements

Qualifications

Requirements:

• Currently enrolled in a BS or MS program in Computer Science, Electrical Engineering, or a related field
• Basic understanding of product management and market analysis methodologies
• Familiar with key major LLMs, AI tools 
• Strong programming skills in Python
• Strong written and verbal communication skills, especially for explaining technical decisions
• Ability to work independently and communicate technical ideas clearly

Additional Skills Preferred (but not required):

• Interest in building AI systems that support human judgment and decision-making, not just generation
• Comfort working with imperfect data, evolving requirements, and subjective evaluation criteria