Intern - HIG PSE IE Management

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 F10A Singapore, 1 North Coast Avenue Singapore 757432 Department High Bandwidth Memory Product and Systems Engineering, Industrial Engineering Management Project Title AI-Enabled High Bandwidth Memory Sample Planning and Workflow Optimization Project Description As an intern in the High Bandwidth Memory Product and Systems Engineering Industrial Engineering team, you will participate in a structured project to improve the visibility and planning of High Bandwidth Memory sample workflows through data analytics, dashboard development, and Artificial Intelligence. The project focuses on mapping the end-to-end sample workflow from Die Bank through probe, test, shipment, and the Reliability Lab. The intern will develop an AI-Enabled solution to predict sample arrival and reliability start dates, forecast burn-in resource demand, automate selected notifications, and provide operational insights through interactive dashboards. The internship provides hands-on exposure to semiconductor sample logistics, process documentation, predictive analytics, business intelligence, and workflow optimization. The intern will collaborate with engineering, planning, operations, and information technology stakeholders to translate data insights into practical improvement recommendations. Objective of the Project • Map and analyze the end-to-end High Bandwidth Memory sample workflow from Die Bank to the Reliability Lab. • Develop predictive models for sample arrival and reliability start dates. • Forecast burn-in and reliability resource demand to improve planning. • Create dashboards and automated notifications that improve sample visibility and risk monitoring. • Identify opportunities to improve workflow efficiency through data analytics and AI-Enabled solutions. Opportunities for Full Time Employment High-performing interns who demonstrate strong technical capability, learning agility, and successful project outcomes may be considered for future internship or full-time employment opportunities, subject to business needs and hiring requirements. Project Scope • Map and document the end-to-end High Bandwidth Memory sample workflow across Die Bank, probe, test, shipment, and reliability operations. • Collect, clean, and analyze sample-management data from relevant manufacturing and planning systems. • Develop predictive models and automated notifications for sample arrival, readiness actions, and reliability start dates. • Build Power BI or Tableau dashboards for work-in-progress tracking, resource forecasting, capacity visibility, and execution-risk monitoring. • Identify workflow bottlenecks and recommend opportunities for process improvement and automation. Learning Opportunities • Gain exposure to High Bandwidth Memory sample logistics and semiconductor reliability operations. • Develop practical experience in data preparation, predictive modelling, dashboard development, and workflow automation. • Learn how Manufacturing Execution Systems and enterprise planning systems are used to manage manufacturing information. • Strengthen process-mapping, structured problem-solving, technical documentation, and stakeholder-communication skills. • Explore applications of Artificial Intelligence and AI-Enabled workflows in semiconductor planning and operations. Deliverables • End-to-end High Bandwidth Memory sample-flow map and process documentation. • AI-Enabled sample-arrival and reliability start-date prediction model. • Automated alert prototype for upcoming sample arrivals and readiness actions. • Burn-in capacity forecasting and sample-status dashboard. • Final report and presentation outlining findings, model performance, recommendations, and potential automation opportunities. Impact of the Project • Improve visibility and traceability across the High Bandwidth Memory sample workflow. • Enable earlier planning for sample arrivals, reliability activities, and burn-in resource requirements. • Enhance data-driven decision-making through predictive analytics and interactive dashboards. • Identify opportunities to reduce manual reporting and improve workflow efficiency. Skillsets Required • Strong analytical thinking and structured problem-solving skills. • Familiarity with data-analysis and visualization tools such as Excel, Power BI, Tableau, Python, or Structured Query Language. • Interest in semiconductor manufacturing, sample logistics, workflow optimization, and business intelligence. • Familiarity with machine learning, Artificial Intelligence tools, or AI-Enabled workflows is advantageous. • Good communication, teamwork, documentation, and presentation skills. Course of Interest The ideal candidate should be pursuing a Bachelor’s or Master’s Degree in Industrial Engineering, Systems Engineering, Computer Science, Data Science, Business Analytics, or a related field. Duration of Period The ideal candidate should be able to commit to a full time internship period of 5 months from the months of Jan to May 2027. About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all . With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our peop…