KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us. Group/Division With over 40 years of semiconductor process control experience, chipmakers around the globe rely on KLA to ensure that their fabs ramp next-generation devices to volume production quickly and cost-effectively. Enabling the movement towards advanced chip design, KLA's Global Products Group (GPG), which is responsible for creating all of KLA’s metrology and inspection products, is looking for the best and the brightest research scientist, software engineers, application development engineers, and senior product technology process engineers. The Broadband Plasma Division (BBP) provides market-leading patterned wafer optical inspection systems for leading-edge IC manufacturing. Logic, foundry, and memory customers depend on BBP products to detect yield-critical defects for process debug and excursion monitoring at advanced process nodes. BBP flagship products include the 29xx and 39xx series which leverage Broadband Plasma technology to capture a wide range of defects with ultimate sensitivity at the optical inspection speeds needed for inline defect monitoring. Job Description/Preferred Qualifications Key Objectives: Develop a chatbot capable of answering questions about historical software bugs, feature requests, or documentation using semantic search and RAG. Build an intelligent agent that automatically classifies and prioritizes new issues, and recommends appropriate actions (e.g., assignment, escalation, deferral). Integrate conventional and vector databases to manage structured and unstructured data. Apply natural language processing (NLP) techniques to extract meaningful insights from issue descriptions and metadata. Technologies & Tools: Microsoft Graph Connectors Python, LangChain or LlamaIndex Vector databases (e.g., Pinecone, Qdrant, Weaviate) Embedding models (e.g., SentenceTransformers, OpenAI) Conventional databases (e.g., PostgreSQL, MongoDB) Large Language Models (e.g., GPT-4, Claude) Learning Outcomes: Hands-on experience with modern AI tools for workflow automation. Exposure to real-world software engineering data and processes. Understanding of RAG systems and intelligent decision support. Skills in data engineering, NLP, and conversational AI.