Intern Test Solutions Engineer Jobs

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 . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. At Micron, our vision is to transform how the world uses information to enrich life for all. As a global leader in memory and storage innovation, we accelerate the transformation of information into intelligence, enabling advances in learning, communication, and technology. Micron's Boise site is at the center of a historic semiconductor manufacturing expansion, supported by a $15 billion investment. This growth creates exciting opportunities for students to contribute to leading-edge DRAM manufacturing while developing technical expertise in one of the world's most advanced fabrication environments. The ID1 High Volume Manufacturing Process Engineer supports process quality, yield improvement, manufacturing efficiency, and cost reduction within a high-volume semiconductor fabrication environment. This role partners closely with equipment engineers, manufacturing teams, process owners, and operations leaders to find opportunities, resolve process issues, and optimize wafer output. The successful candidate will apply statistical analysis, engineering principles, and data-driven decision making to improve manufacturing performance, support operational excellence, and contribute to key area performance indicators. Responsibilities Monitor, analyze, and improve manufacturing processes to achieve yield, quality, throughput, and cost objectives. Apply SPC, FDC, Design of Experiments, and systematic problem-solving methodologies to identify and resolve process deviations and chronic is

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 . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Job Description Micron is seeking driven Process Technicians to support wafer manufacturing operations by monitoring processes, reviewing data, and partnering with engineering and production teams to enhance yield, quality, and overall efficiency. This position requires strong analytical and problem‑solving abilities, along with the capability to troubleshoot issues and manage shifting priorities in a fast‑paced environment while adhering to established procedures. Qualified candidates will have intermediate computer skills, including proficiency with Microsoft Office, and experience extracting, analyzing, and effectively communicating data insights. Success in this role relies on strong teamwork and communication, solid organization and time‑management skills, the ability to work independently with minimal supervision, and flexibility regarding responsibilities and shift assignments. As part of the fabrication team driving innovation for a global leader in memory and storage solutions, Process Technicians play a key role in manufacturing excellence while demonstrating reliability, engagement, and a growth mindset that aligns with Micron’s core values: People, Innovation, Tenacity, Collaboration, and Customer Focus. Responsibilities: Complete all required safety training, work safely in various environments (including uneven terrain and confined spaces), and respond to potential hazards to prevent accidents. Manage semiconductor tools, cond

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 . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Project Title: Development of an AI-Driven Reliability Analytics and Automation Framework for NAND Product Engineering Description This project aims to use an already developed intelligent analytics and automation framework to enhance efficiency, decision-making, and productivity within NAND Reliability Engineering. The intern will leverage data analytics, artificial intelligence (AI), and software automation techniques to process large volumes of reliability and qualification data, identify trends, and generate actionable engineering insights. Key responsibilities include: Analyzing NAND reliability and qualification datasets to identify patterns and improvement opportunities. Presenting technical findings and recommendations to engineering teams. Scope of Work - Execution of MAF/ULR wave tests - Log collection and analyzing - Level-1 Failure Analysis Supporting team NAND Intrinsic Reliability (NIR) Team (Primary) Global Quality & Reliability Engineering (QRE) Team Test Program Development Team Deliverables Technical Documentation User guide, architecture overview, and maintenance documentation. Source code repository with appropriate documentation. Final Presentation Presentation summarizing project objectives, methodology, results, lessons learned, and future enhancement opportuni

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

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 SSD Assembly Process & Equipment Engineering Project Title AI-Enabled SSD Depanel Process Characterization and Optimization Project Description This internship project focuses on characterizing process variations in SSD depanel operations within a high-volume manufacturing environment. The project aims to deepen understanding of the interactions between process parameters, equipment performance, and product quality outcomes. The intern will undertake a structured engineering project involving Design of Experiments (DOE), statistical analysis, process characterization, and data-driven optimization techniques. In addition, the intern will explore AI-Enabled approaches to improve engineering productivity, automate data interpretation, and accelerate insight generation from process characterization activities. The project provides an opportunity to gain hands-on experience in process engineering, equipment operations, and advanced manufacturing technologies within the semiconductor industry. Objective of the Project Characterize key process variables affecting SSD depanel performance and product quality. Establish a robust op

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 Manufacturing Wet Process Engineering (MFG WET) Project Title AI-Enabled Germhold Reduction for Dry Strip Workstation Project Description This internship project focuses on leveraging data analytics and AI-Enabled methodologies to understand and reduce equipment Germholds within the Dry Strip workstation in a semiconductor manufacturing environment. The project aims to identify key factors contributing to Germhold occurrences, develop data-driven insights, and evaluate opportunities to improve workstation efficiency and manufacturing capacity. The intern will gain hands-on experience working with operational datasets, engineering teams, and manufacturing equipment while exploring the application of Artificial Intelligence, machine learning, and predictive analytics within semiconductor manufacturing processes. Objective of the Project Identify key drivers and trends associated with equipment Germholds in the Dry Strip workstation. Apply data analytics and machine learning techniques to uncover opportunities for Germhold reduction. Develop a structured methodology to improve understanding of equipment performance and opera

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. The Solutions Engineer Intern sits within the Transform the Business pillar of the Quality Systems organization, supporting the AI Process Intelligence (AIPI) team. This role is ideal for students or recent graduates in Computer Science, Data Science, Software Engineering, or related technical fields who are curious, eager to learn, and excited about AI and automation. You will work closely with and under the guidance of senior Solutions Engineers and Process Architects, participating in defined project tasks, testing activities, documentation, and proof-of-concept development. You are not expected to independently lead projects — you are expected to learn fast, contribute meaningfully, and grow your skills in a structured and supportive environment. Department Global Quality Systems – Solutions Engineering Project Title AI‑Driven Automation and Knowledge Integration – Solutions Engineering Internship Project Description This internship is a learning‑focused, project‑based role designed to provide hands‑on exposure to AI‑enabled automation and enterprise system integration within Micron’s Quality Systems domain. The project focuses on designing and developing prototype‑level automation and AI agent

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 Device Engineering Project Title AI-Enabled Device Characterization Automation and Intelligent Engineering Workflow Platform Project Description As an AI / Data Science Intern in the NAND Device Engineering organization, you will participate in the development of AI-Enabled solutions that enhance engineering productivity, accelerate device characterization, and improve data-driven decision-making for advanced 3D NAND technologies. This internship provides an opportunity to apply Artificial Intelligence, machine learning, data science, and automation techniques to complex semiconductor engineering datasets. The project focuses on developing intelligent automation workflows, AI-assisted analysis platforms, and Agentic AI solutions that streamline device characterization activities, automate engineering insights generation, and improve project execution efficiency. Working alongside experienced engineers, you will gain exposure to semiconductor device development, large-scale data analytics, and emerging Generative AI technologies within a manufacturing and product development environment. Objective of the Project Develop an AI-Enabled platform that automate

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. The HBM Physical Design team is responsible for implementing advanced High Bandwidth Memory (HBM) SoC and base die designs that enable next-generation AI, high-performance computing, and data center solutions. The team collaborates across architecture, RTL, verification, DFT, and signoff engineering to deliver high-performance, power-efficient silicon while developing innovative design methodologies and automation solutions. As an SoC Physical Design Intern on the HBM team, you will work alongside experienced engineers to support the implementation of advanced HBM SoC designs. You will gain hands-on experience with physical design methodologies, timing analysis, signoff flows, and automation while contributing to the development of next-generation memory products that power AI and high-performance computing applications. Responsibilities Support the physical implementation of SoC design blocks, including floorplanning, placement, clock tree synthesis, routing, and physical optimization activities. Analyze timing, power, area, congestion, and physical verification results to find opportunities for design improvement and optimization. Assist with static timing analysis, timing closure, and debugging across multiple operating modes and process corners. Develop and enhance automation tools, scripts, reports, and workflows using Python, Tcl, shell scripting, and AI-assisted solutions. Collaborate with multi-functional engineering teams to document r

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 Description This internship supports engineering teams across Micron Singapore in improving manufacturing processes, equipment performance, yield, quality, reliability, and operational efficiency. Successful candidates may be assigned to projects within Process Engineering, Equipment Engineering, Manufacturing Engineering, Quality Engineering, Industrial Engineering, or related engineering functions. Where applicable, interns may utilize Artificial Intelligence (AI), Generative AI, automation technologies, advanced analytics, or digital manufacturing tools to improve engineering efficiency and decision-making. Objective of the Project Improve manufacturing processes and operational performance. Support equipment optimisation and reliability initiatives. Analyse production data and identify improvement opportunities. Develop engineering solutions to improve yield, quality, productivity, and cost performance. Support continuous improvement and operational excellence activities. Job/Project Scope Inte

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 Fab 10, 1 North Coast Drive Department F10 Facilities Project Title Exhaust Plume Detection and Reduction Through Mechanical Engineering Analysis Project Description This internship provides an opportunity to participate in an engineering study focused on the characterisation, detection, and mitigation of exhaust plumes within a semiconductor manufacturing environment. The project involves evaluating plume formation mechanisms, assessing potential detection methods, and investigating engineering approaches to reduce or eliminate visible plume conditions. The intern will apply mechanical engineering principles, data analysis, and engineering evaluation techniques to support the study while gaining exposure to facilities systems, sustainability initiatives, and energy-efficiency opportunities. Objective of the Project Investigate factors that contribute to exhaust plume formation. Evaluate suitable methods for plume detection and characterisation. Assess engineering approaches for plume reduction or elimination. Identify potential energy-efficiency opportunities associated with mechanical exhaust systems. </