Intern - FE Materials Procurement Operations

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Singapore Department Front End Capital Procurement Operations Project Title AI-Enabled Supplier Performance Analytics and Procurement Process Transformation Project Description This internship project focuses on developing data-driven and AI-Enabled solutions to improve supplier performance visibility, procurement analytics, and process efficiency within Front End Capital Procurement Operations. The intern will undertake a structured project involving supplier performance analysis, capital equipment delivery tracking, procurement dashboard development, and workflow optimization. The intern will also explore how Artificial Intelligence, Generative AI, AI Assistants, and Agentic AI can improve data analysis, reporting, knowledge retrieval, and decision-making. Objective of the Project Develop an analytical framework that improves visibility into supplier performance, capital equipment delivery, and procurement activities. Apply data analytics and AI-Enabled methodologies to identify supply risks, operational trends, and improvement opportunities. Evaluate procurement workflows and recommend opportunities for process simplification, standardizat

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Singapore – Fab10 (1 North Coast Drive, Singapore 757432) Department Fab10 High Volume Manufacturing Photo – Process and Equipment Engineering Project Title AI Agents for High Volume Manufacturing Photo Productivity and Automation Project Description High Volume Manufacturing Photo engineers perform engineering activities involving data collection, issue investigation, report generation, action tracking, and knowledge retrieval. This project provides the intern with an opportunity to explore how AI-enabled solutions can streamline selected engineering workflows, generate intelligent insights, and improve operational efficiency. The intern will collaborate with Photo engineers to understand engineering challenges, identify suitable automation opportunities, and develop project-based AI and Python solutions. The intern will also prototype AI Agents for selected use cases involving troubleshooting, workflow management, reporting, knowledge retrieval, and decision-making. Through this project, the intern will gain practical exposure to Artificial Intelligence, Large Language Models, Generative AI, Python automation, data analytics, and semiconductor manufacturing engineering. Objective o

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Micron F10, 1 North Coast Drive. Department Process and Equipment Engineering (Diffusion) Project Title F10 CMOS Matching and RegE Wafer Edge Exclusion Programme Project Description The Process and Equipment Engineering Intern will participate in an engineering project focused on CMOS matching analysis and wafer edge yield enhancement within advanced semiconductor manufacturing processes. Working alongside Process and Equipment Engineers, the intern will gain hands-on exposure to yield learning methodologies, inline process monitoring, defect characterization, and data-driven manufacturing optimization. The project provides opportunities to investigate process variations, evaluate wafer edge performance, and develop analytical solutions that enhance manufacturing quality and yield performance. The project combines semiconductor process engineering fundamentals with advanced data analytics, automation, and AI-enabled engineering tools to accelerate learning, improve engineering efficiency, and drive fact-based decision making. The internship provides exposure to: Semiconductor manufacturing processes and process integration. Yield analysis, defect characterization, and process m

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Singapore Department NAND Probe Product Engineering Project Title AI-Enabled Test Mode Innovation and Integration Project Description The NAND Probe Product Engineering Intern will undertake a structured learning and innovation project focused on test mode development concepts, silicon validation methodologies, and AI-Enabled engineering solutions for advanced NAND technologies. Working alongside experienced Product and Design Engineers, the intern will develop knowledge of NAND test methodologies, Design for Test (DFT) concepts, and silicon validation processes. This internship combines semiconductor engineering fundamentals with Artificial Intelligence, data analytics, automation, and Generative AI technologies, providing an opportunity to explore how AI-Enabled tools and Agentic AI solutions can enhance engineering learning, technical knowledge discovery, test effectiveness, and innovation. Objective of the Project The intern will have the opportunity to: Develop an understanding of NAND architecture, probe testing concepts, Design for Test methodologies, and test mode integration practices. Explore engineering datasets to identify product behaviour

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Singapore Department Advanced Technology Singapore, Alpha Technology Engineering Part Type Management Project Title Fab 10 Metallization Conversion and M77R New Product Introduction Program Management Project Description The intern will undertake a project focused on the Fab 10 Metallization sister fabrication facility conversion and the M77R new product introduction. The project provides practical exposure to semiconductor manufacturing, process integration, program planning, risk management, and stakeholder coordination. The intern will work with engineering and manufacturing teams to track project readiness, analyze technical information, and develop clear program-management materials. Objective of the Project To establish a structured program-management approach for the Fab 10 Metallization conversion and M77R product introduction, enabling effective milestone tracking, early risk identification, manufacturing-readiness assessment, and cross-functional communication. Opportunities for Full Time Employment Successful interns may be considered for future full-time opportunities within Micron’s engineering and manufacturing organizations. Consideration will be subject to internshi

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Singapore Department Process and Equipment Engineering, Chemical Vapor Deposition (CVD) Project Title Workstation Performance Acceleration Through an Artificial Intelligence-Driven Root Cause Analysis Tool Project Description The intern will explore the application of Artificial Intelligence and machine learning to incident analysis within the Chemical Vapor Deposition process area. The project aims to transform equipment, process, and human-written incident data into structured, actionable insights that enable engineering teams to investigate recurring workstation failures more effectively. Through this project, the intern will gain exposure to semiconductor process and equipment engineering while developing and validating an AI-Enabled root cause analysis solution. The experience will involve technical learning, data analysis, model experimentation, and cross-functional engagement with production, equipment, process, hardware, and planning subject-matter experts. Objective of the Project Develop an AI-Enabled approach for interpreting human-written incident records from the Equipment Tracking Interface (ETI). Organize incident data into meaningful Pareto categories to provi