F10 Probe Process Engineer in Fab 10n X

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. Responsibilities: Perform cross-section analysis and Scanning Electron Microscopy (SEM) inspection to monitor process health and ensure production quality. Handle Transmission Electron Microscopy (TEM) sample preparation using Focus Ion Beam (FIB) for detailed TEM inspection. Identify defects and failure mechanisms through physical failure analysis using a variety of sample de-processing techniques and a wide range of failure analysis equipment. Complete physical fault isolation techniques to pinpoint and resolve issues that may impact production efficiency. Collaborate with engineering teams to provide timely feedback and implement solutions to maintain efficient production tool performance. Support the analysis of wafers with functional failures by applying various Failure Analysis tools and techniques to isolate defects and identify root causes. Preserve comprehensive documentation of analytical findings and approaches to aid continual progress initiatives. Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and

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. Responsibilities: Conducting technical tests and experiments for process and R&D engineering in the wafer fabrication sector of semiconductor manufacturing. Setting up semiconductor processing equipment to strict specifications. Monitoring, auditing, and providing mentorship to line operators to achieve world-class results. Processing test runs and preparing detailed records, charts, and graphs of results for presentation to engineering, aimed at identifying yield problems or testing new products. Working on Fab equipment and processes to ensure outstanding performance. Tracking, preserving, and refining equipment and processes via basic troubleshooting of tool issues. Analyzing and disposing out-of-control events in accordance with established SPC rules for both tool qualification and product measurements. Assisting engineering requests through testing and experimenting on processes and equipment, while carefully gathering, recording, and examining data from these tests and experiments. Assisting in the installation, relocation, and upgrades of tools. Improving tool uptime through quality detailed problem solving and troubleshooting. <l

TECHNOLOGIST - F10 MFG EQUIPMENT — Fab 10N/X, Singapore. Apply via Workday.

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 Singapore, Fab 10 (1 North Coast Drive, Singapore 757432) Department Photolithography Process and Equipment Engineering Project Title AI-Enabled Quality Drift Detection and Engineering Workflow Automation Project Description Advanced data analytics and machine learning are increasingly used in semiconductor manufacturing to improve efficiency, process control, and quality performance. This internship project focuses on applying data analytics and machine learning techniques to large-scale quality datasets for faster detection of quality-metrics drift. The intern will contribute to an end-to-end solution covering data querying, preprocessing, analytics, modelling, and results visualization. Objective of the Project Develop analytical models for monitoring key quality metrics and detecting potential drift. Apply machine learning and multivariable analysis to large-scale test and measurement data. Create automated workflows that improve engineering productivity and analytical efficiency. Develop visualizations that communicate model results and quality trends effectively. Opportunities for Full Tim

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 F10 Singapore, 1 North Coast Drive Department Advanced Device Technology and Systems, Process and Equipment Engineering, Wet Process Project Title Wet Process Defectivity and Etch Rate Stability Improvement Project Description This internship project focuses on evaluating process conditions and equipment parameters to identify optimal solutions for reducing manufacturing defects, improving material etching uniformity, and enhancing process robustness within wet etch operations. The project involves structured characterization studies to develop an understanding of process and equipment behavior and evaluate techniques for reducing defectivity and process variation. Through data analysis, guided experimentation, and AI-Enabled learning, the intern will develop foundational knowledge of wet processes, equipment architecture, and semiconductor manufacturing. Objective of the Project Identify process and equipment factors that influence defectivity, etch rate uniformity, and process stability. Evaluate potential process and equipment improvements through structured characterization and data analysis. Develop recommendations that improve process robustn

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 1 North Coast Drive, Singapore Department F10 Process and Equipment Engineering, Chemical Vapour Deposition Module Project Title Big Data Analysis of Wafer Bevel Wafer Intelligent Scanner Metrics for Defect Reduction Project Description The Wafer Intelligent Scanner collects inspection data from the edge, or bevel, of wafers during semiconductor manufacturing. This internship project uses data analytics to study Wafer Intelligent Scanner metrics, identify patterns linked to defects, and determine early warning indicators that may help prevent future yield issues. The goal is to transform large volumes of inspection data into actionable insights that enable engineers to detect potential issues earlier and reduce wafer defects. The intern will gain practical exposure to semiconductor process and equipment engineering, defect analysis, machine learning, and AI-Enabled manufacturing analytics. Objective of the Project Identify Wafer Intelligent Scanner metrics associated with wafer defects and yield loss. Develop a data-driven methodology for detecting abnormal wafer bevel behaviour. Evaluate statistical, machine learning, and Artificial Intelligence t

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 Singapore, Fab 10N (1 North Coast Drive, Singapore 757432) Department Process Integration Engineering Project Title AI-Enabled Inline Health Monitoring and Process Drift Detection Project Description This internship project focuses on developing and enhancing an inline health-monitoring system for Process Integration. Through close mentorship and hands-on learning, the intern will extract and organize relevant inline metrics, targets, and specifications, and develop visualizations for process-health monitoring. The intern will gain exposure to semiconductor Process Integration by analyzing process data and exploring Micron-qualified Artificial Intelligence tools. The project will also evaluate opportunities to automate selected parts of the inline monitoring workflow, improve drift detection, and enhance engineering productivity. Objective of the Project Develop an AI-Enabled inline health-monitoring and process drift-detection solution. Improve the visualization of inline metrics, targets, specifications, and process-health trends. Explore Artificial Intelligence applications for process-window optimization and e

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. Job Responsibilities: Lead on site Smart Fac transformation and on implementation of Smart fac projects in collaboration with other Micron sites/Departments/sections Plan, schedule and supervise Preventive and Corrective Maintenance work activities, priorities and reallocate resource when required, on mechanical equipment and Instrumentation & Control system under the responsibilities of Facilities organization Lead troubleshooting and attend to abnormalities in support of Operations in a timely manner on system under the responsibilities of Facilities organization, when required Lead and participate in equipment and system abnormalities root cause analysis, attend review meeting and provide update, then execute corrective and preventive action for continual improvement, this include installation and modification work on existing or new mechanical equipment and Instrumentation & Control system Support engineering and tool install on system capabilities analysis during scenario evaluations Generate and maintain Scope-of-Work documentation for out sourced contract service Manage out sourced contract service provider to perform work activities in accordance to service agreement Utilize computer base software to document and analyse

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. Department Thin Films Process Engineering (Chemical Vapor Deposition) Project Title Crater Defect Reduction in Tetraethyl Orthosilicate (TEOS) Chemical Vapor Deposition Process Project Description Crater defects observed in the Tetraethyl Orthosilicate (TEOS) Chemical Vapor Deposition (CVD) process pose yield and integration risks in high‑volume semiconductor manufacturing. This internship project focuses on developing a structured understanding of crater defect mechanisms by integrating process knowledge, chamber condition review, and manufacturing data analytics. The intern will work on a defined engineering problem and apply data‑driven methodologies and controlled experimentation to identify defect contributors and evaluate improvement opportunities within the Fab10 TEOS CVD process. Objective of the Project Build a fundamental understanding of the TEOS CVD process flow and chamber condition effects Apply data analysis techniques to characterize crater defect signatures and trends Develop hypothesis‑driven insights linking process conditions to defect formation Evaluate defect reduction opportunities while maintaining critical film performance requirements <

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. Responsibilities: As part of the manufacturing team, you will be - Responsible for analyzing machines utilization, improving and ensuring quality output. Maintain overall production efficiencies of assigned workstations Support a safe work environment by following safety procedures and promptly reporting identified hazards. Work alongside Equipment engineers to strengthen and maintain equipment availability to meet stringent product requirements. Requirements: A relevant Diploma in Engineering OR equivalent working experience Self-motivated, results-oriented, and looking for growth Proficient in Microsoft Office Comfortable with doing 12-hr shift 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,

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. As the Facilities SmartFac & Control Engineer, you are required to lead engineering and maintenance works in the fields of SMART Fac and Control systems on site, with the necessary guidance and direction from Facilities organization, to achieve facilities department, site, facilities corporate and company goals. Job Responsibilities: Lead on site Smart System transformation and on implementation of Smart fac projects with AI-enabled detection and analytics in collaboration with other Micron Departments. Lead on Sustainability and Environmental Control system deployment with early detection and predictions, utilizing Industry 4.0 system. Lead on labor productivity automation projects with innovative idea to improve facilities team efficiency. Plan, design and lead Control Automation engineering projects includes new construction, system upgrading and quality improvement. Lead troubleshooting and attend to abnormalities in support of Operations in a timely manner on system under Smart FAC & Control section w

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. Job Posting Title: Intern - F10 Process and Equipment Engineer Location: F10 Singapore, 1 North Coast Drive Department: Process and Equipment Engineering Project Title: Workstation Defects Improvement Evaluation Project Description: This internship project focuses on evaluating material solutions and process conditions to reduce manufacturing defects and improve process robustness within dry etch operations. The project centres on studying synthetic quartz rings and periodic conditioning techniques to understand their impact on defect performance and process stability. Through structured analysis, guided and AI assisted learning, the intern will develop foundational knowledge of dry etch process behaviour, tool architecture, and material interactions relevant to semiconductor manufacturing. Project Scope: The objective is to provide the intern with hands‑on learning exposure to dry etch process fundamentals while developing analytical thinking, en

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. Project Title Diffusion Capacity Optimization Through Constraint Workstation Improvement Project Description This internship provides an opportunity to work on projects focused on improving capacity and operational efficiency within the Diffusion manufacturing area. The intern will analyze manufacturing data, evaluate workstation performance, investigate recurring production constraints, and develop recommendations to improve equipment utilization, manufacturing throughput, and cycle time performance. The project will provide exposure to manufacturing engineering methodologies, capacity management, statistical analysis, and cross-functional collaboration within a semiconductor manufacturing environment. Objective of the Project Analyze Diffusion manufacturing performance and capacity utilization. Identify workstation constraints that impact throughput and cycle time performance. Investigate key sources of capacity loss and evaluate improvement opportunities. Develop data-driven recommendations to improve operational efficiency and manufacturing performance. Opportunities for Full Time Employment Successful interns who demonstrate strong analytic

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 Device Technology and Systems, Advanced Technology Enablement Dry Etch, F10 Project Title Dry Etch Process Performance Optimization Using Data Analytics and Artificial Intelligence Project Description Dry etch is a critical semiconductor manufacturing process that has a significant impact on product yield, cycle time, and manufacturing capacity. This internship project focuses on applying process engineering, data analytics, and AI-Enabled methods to understand process behavior, identify performance gaps, and develop improvement recommendations. The intern will work with manufacturing, equipment, and process datasets to explore opportunities related to process stability, productivity, and yield. The project will provide practical exposure to dry etch process engineering, industrial data analytics, data visualization, and Artificial Intelligence applications. Objective of the Project Analyze dry etch process and equipment performance using manufacturing data. Identify sources of process variation, performance drift, productivity loss, and yield impact. Develop data-driven recommendations for improving process stability

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 Equipment Engineering (PEE) Project Title AI-Enabled CMP Equipment Health & Breakage Risk Prediction Dashboard Project Description Chemical Mechanical Planarization (CMP) tool performance directly influences wafer quality, equipment reliability, and manufacturing efficiency. This project focuses on developing an AI-Enabled dashboard that integrates fab equipment and manufacturing data to identify early indicators of wafer breakage, equipment degradation, and yield excursions. The intern will work on data exploration, predictive analytics, and visualization techniques to develop an intelligent monitoring solution that enables proactive decision-making. Through this project, the intern will gain exposure to semiconductor manufacturing equipment, reliability engineering methodologies, Artificial Intelligence applications, and data-driven engineering practices within a high-volume manufacturing environment. Objective of the Project Develop an AI-Enabled equipment monitoring and risk prediction dashboard capable of identifying potential CMP tool-related wafer breakage and excursion risks before significant manufacturing impact occurs. Oppo