AI Intern

DescriptionAdvantest 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 emergingAI systems and integrating them into Advantest's advanced testingplatforms.Location: Austin, TX or San Jose, CA (headquarters)Role OverviewIn 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 ResponsibilitiesDesign 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 baselinesIdentifying conflicts, gaps, redundancies, or lack of noveltyProducing structured assessments and constructive feedbackExperiment 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 fieldStrong programming skills in PythonHands-on experience with LLMs, including prompt design and experimentationFamiliarity with retrieval-augmented generation (RAG) concepts (e.g., embeddings, vector search, context assembly)Experience or coursework involving multi-step workflows, pipelines, or agent-based systemsStrong written and verbal communication skills, especially for explaining technical decisionsAbility to work independently and communicate technical ideas clearlyAdditional Skills Preferred (but not required):Experience with agent orchestration frameworks (e.g.,LangGraph, LangChain, custom agent loops)Exposure to LLM evaluation techniques, including rubric-based scoring, pairwise comparison, or ranking tasksExperience working with document-heavy or text-analysis problems (e.g., reviews, reports, proposals, research papers)Familiarity with semantic similarity, novelty detection, or content comparison techniquesInterest in building AI systems that support human judgment and decision-making, not just generationComfort working with imperfect data, evolving requirements, and subjective evaluation criteria