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  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

* Design and implement multi-step agentic workflows for analyzing and evaluating technical content.

* Develop RAG-based pipelines that combine internal documentation and reference materials with LLM reasoning.

* Build AI agents capable of:

* Comparing proposed ideas or approaches against known solutions or baselines

* Identifying conflicts, gaps, redundancies, or lack of novelty

* Producing structured assessments and constructive feedback

* Experiment with prompting strategies, planning, reflection, and tool usage to improve reasoning quality and consistency.

* Evaluate and iterate on system performance using qualitative and semi-quantitative metrics.

* Collaborate with engineers and researchers to translate ambiguous evaluation criteria into actionable AI workflows.

Requirements:

* Currently enrolled in a BS or MS program in Computer Science, Electrical Engineering, or a related field

* Strong programming skills in Python

* Hands-on experience with LLMs, including prompt design and experimentation

* Familiarity with retrieval-augmented generation (RAG) concepts (e.g., embeddings, vector search, context assembly)

* Experience or coursework involving multi-step workflows, pipelines, or agent-based systems

* 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):

* Experience with agent orchestration frameworks (e.g.,Lang Graph, Lang Chain, custom agent loops)

* Exposure to LLM evaluation techniques, including rubric-based scoring, pairwise comparison, or ranking tasks

* Experience working with document-heavy or text-analysis problems (e.g., reviews, reports, proposals, research papers)

* Familiarity with semantic similarity, novelty detection, or content comparison techniques

* 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