Intern - HIG HBM PSE PACKAGE PE

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 20,000 - 29,000; Full time

Job summary

Micron Technology, Inc. in Singapore invites an intern to join the Artificial Intelligence-Enabled High Bandwidth Memory Defect Library and Analytics Dashboard Development project.

You will apply engineering data analytics, Python programming, and dashboard development to organize defect information and present it through an interactive visualization platform. Under the guidance of experienced engineers, you will explore AI-enabled approaches, learn about defect signatures across test flows, and

Qualifications

• Pursuing a master's degree in a relevant engineering or science discipline.
• Proficiency in Python programming and data analysis.
• Strong analytical and problem-solving abilities.
• Interest in AI tools and AI-enabled workflows.

Responsibilities

• Study defect signatures across test flows and create a structured knowledge repository.
• Develop an interactive defect dashboard for standardized categorization and visualization.
• Apply Python and statistics to relate physical defects to electrical results.
• Evaluate AI-enabled methods for defect classification and information retrieval.

Skills

Python programming

Data analytics

Dashboard development

Data visualization

AI tools familiarity

Education

Master's degree in Electrical Engineering or related field

Tools

Python

SQL

Job description

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

Heterogeneous Integration Group, High Bandwidth Memory Product System Engineering

Project Title

Artificial Intelligence-Enabled High Bandwidth Memory Defect Library and Analytics Dashboard Development

Project Description

High Bandwidth Memory products generate significant volumes of engineering, electrical test, and failure analysis data throughout the manufacturing and test lifecycle. Consistent documentation and structured management of defect signatures are important for strengthening engineering knowledge retention, improving information accessibility, and enabling data-driven technical analysis.

This internship project focuses on developing a structured High Bandwidth Memory Defect Library that captures the electrical and physical signatures of selected defect modes across multiple test flows. The intern will apply engineering, data analytics, Python programming, and dashboard-development concepts to organize defect information and present it through an interactive visualization platform.

Under the guidance of experienced engineers, the intern will also evaluate appropriate Artificial Intelligence-enabled approaches, including Generative Artificial Intelligence, Artificial Intelligence Assistants, Agentic Artificial Intelligence solutions, and Large Language Model-based tools. These approaches may be used to improve defect categorization, information retrieval, engineering knowledge management, and insight generation.

The assignment is a supervised, educational, and project-based internship. It is intended to develop the intern’s technical and professional capabilities and does not replace the responsibilities of regular employees.

Objective of the Project

Establish a standardized High Bandwidth Memory Defect Library that documents the electrical and physical signatures of selected defect modes. Develop an interactive dashboard for visualizing, tracking, and analyzing defect information across multiple test flows. Create a consistent data structure and categorization framework that strengthens engineering knowledge retention and information retrieval. Evaluate feasible Artificial Intelligence-enabled methods for improving defect classification, searchability, and technical insight generation.

Opportunities for Full Time Employment

Strong internship performance may provide opportunities for consideration for future full-time employment. Any employment consideration will be subject to business requirements, position availability, candidate suitability, and the applicable recruitment process.

Project Scope

The intern will undertake the following project-based activities under appropriate technical guidance:

• Study the electrical and physical signatures associated with selected semiconductor defect modes and examine how these signatures appear across different process stages and test flows.
• Organize engineering and failure analysis information into a structured, searchable, and reusable defect knowledge repository.
• Develop an interactive dashboard for standardized defect categorization, visualization, trend analysis, and technical reporting.
• Apply Python, statistical methods, and data analytics techniques to examine relationships between physical defect characteristics and electrical test results.
• Evaluate Artificial Intelligence-enabled methods, including Generative Artificial Intelligence, Artificial Intelligence Assistants, Agentic Solutions, and Large Language Models, for defect categorization, information retrieval, and engineering knowledge management.

Learning Opportunities

• Develop knowledge of High Bandwidth Memory technology, semiconductor product engineering, manufacturing processes, and defect mechanisms.
• Learn electrical testing methodologies, failure signature interpretation, defect characterization, and failure analysis concepts.
• Apply Python programming, statistical analysis, data management, dashboard development, and data visualization to an engineering project.
• Explore responsible applications of Artificial Intelligence, Generative Artificial Intelligence, Artificial Intelligence Assistants, Agentic Artificial Intelligence, and Large Language Models in engineering workflows.
• Strengthen technical documentation, engineering communication, presentation, and cross-functional collaboration skills.

Deliverables

• A structured and searchable High Bandwidth Memory Defect Library containing documented electrical and physical signatures for selected defect modes.
• An interactive and user-friendly dashboard that enables standardized visualization, tracking, filtering, and analysis of defect information across multiple test flows.
• A documented defect categorization framework, data structure, and methodology that enable consistent future knowledge capture.
• A technical report describing the project methodology, analytical observations, dashboard functionality, limitations, and recommended future enhancements.
• A final presentation and demonstration communicating the project outcomes, engineering insights, and potential Artificial Intelligence-enabled applications.

Impact of the Project

The project is expected to: Improve the accessibility, consistency, and usability of defect-related engineering information. Strengthen visibility and understanding of defect signatures across selected test flows and process stages. Enable more efficient technical investigation, information retrieval, and knowledge transfer. Establish a scalable foundation for future data analytics and Artificial Intelligence-enabled engineering knowledge-management initiatives.

Skillsets Required

• A degree-level foundation in electrical engineering, materials science and engineering, semiconductor technology, physics, data science, or a related engineering or science discipline.
• Proficiency in Python programming and an understanding of data processing, statistical analysis, or engineering data applications.
• Strong analytical, critical-thinking, and problem-solving capabilities, with the ability to organize and interpret complex technical information.
• Familiarity with data analytics, data visualization, dashboard development, database concepts, or knowledge-management methods.
• Interest in and familiarity with Artificial Intelligence tools or AI-enabled workflows, such as Generative Artificial Intelligence, Artificial Intelligence Assistants, Agentic Artificial Intelligence solutions, and Large Language Models.

Course of Interest

The ideal candidate should be pursuing a master's degree in electrical engineering, Materials Science and Engineering, Semiconductor Technology and Operations, Physics, Data Science with Semiconductor Applications, or a related engineering or science discipline.

Duration of Period

The ideal candidate should be able to commit to a full-time internship period of at least 6 months.

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 people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities - from the data center to the intelligent edge and across the client and mobile user experience.

Application Information

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

To request assistance with the application process and/or for reasonable accommodations, please contact [e-mail].

Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.

Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.

To learn more, please visit micron.com/careers.