AI Software Engineer Intern

개요 SemiAI is a deep-tech AI company building software for semiconductor manufacturing. Our platform, SMILE, combines AI tools for manufacturing analysis, virtual metrology, and root-cause investigation into an agentic system designed to help semiconductor engineers detect process issues earlier and investigate problems faster. We're a small team working directly on technology that goes into real semiconductor customer proof-of-concept projects. We're looking for an AI Engineer Intern who is genuinely excited about building with LLMs, agents, and AI systems. You don't need a semiconductor background. What matters more is that you enjoy learning unfamiliar technical domains, working with messy real-world data, and figuring things out when the requirements aren't perfectly defined. This is a builder role. You'll build, test, debug, and improve AI systems that are used in internal development and customer POCs. Personal projects count. We care more about what you've actually built than whether the experience came from a previous job. 주요 업무 AI Engineer Intern - Agentic AI and Semiconductor Manufacturing Build agents and LLM-powered tools — tool calling, retrieval, planning loops, structured outputsDesign the evaluations that tell you whether the system actually works, not just whether it ranExplore and clean real customer data: undocumented columns, missing values, sensor noiseBuild and test models on process data — and be honest about what the numbers meanTurn prototypes into things your teammates can run, with documentation that holds upPresent a weekly demo: what you built, what broke, what you learned 자격 요건 Current student or recent graduate in Computer Science, Data Science, Engineering, Statistics, Physics or a related fieldStrong Python — comfortable with pandas and NumPy, and comfortable reading code you didn't writeHands-on experience building with LLMs: API calls, prompting, tool use, retrieval, or agent loops. Personal projects count fully.Solid ML fundamentals — train/validation/test discipline, evaluation metrics, and an instinct for when a result looks too good to be trueFluent with AI coding tools such as Claude Code, Cursor or Copilot, and thoughtful about where you trust them and where you don'tReal curiosity about a physical, industrial domain you've never worked inAuthorized to work in the United States 우대 사항 You've built something agentic end to end — a multi-step agent, an MCP server, a RAG pipeline, an eval harnessExperience with agent or LLM frameworks: LangGraph, LlamaIndex, the OpenAI or Anthropic SDKs, MCPExperience with evaluation and observability tooling — LangSmith, Weights & Biases, Braintrust, or something you wrote yourselfTime-series or sensor data experienceVector databases, embeddings, fine-tuningAny exposure to manufacturing, hardware, physics or industrial data 전형 절차 01서류 전형02면접 전형03합격자 발표