Intern - HIG HBM Component Validation

Micron Technology, Inc.; Singapore; On-site; SGD 20,000 - 27,000; Full time

Job summary

Micron Technology, Inc. in Singapore is offering an internship to develop a scalable analytics platform for HBM component validation.

The project involves building a web-based dashboard that connects validation and production data sources, enabling interactive analytics, AI-enabled insights, and traceability across multiple databases and engineering tools. The intern will gain hands-on experience in data engineering, dashboard development, and AI-driven engineering solutions, with potential

Qualifications

• Familiarity with Python and/or Java for data processing, automation, and system integration.
• Experience with Tableau or similar data visualization platforms.
• Understanding of database concepts, SQL, and relational data modeling.
• Basic knowledge of data analytics and visualization best practices.

Responsibilities

• Design and develop a web-based dashboard capable of querying and visualizing data from multiple engineering databases.
• Develop data models and relational database structures to enable scalable and efficient data integration.
• Establish connections with existing Component Validation dashboards to improve data accessibility and traceability.
• Implement event-based notification mechanisms for predefined validation or test coverage conditions.

Skills

Python

Java

SQL

Tableau

Education

Bachelor's or Master's degree in Computer Science

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, F10A Department Heterogeneous Integration Group (HIG) – High Bandwidth Memory (HBM) Product System Engineering (PSE)

Project Title

Development of a Component Validation Test Development Dashboard

Project Description

This internship project provides an opportunity to develop a scalable analytics platform that enhances visibility into High Bandwidth Memory (HBM) component validation activities. The intern will gain hands-on experience in data engineering, dashboard development, and AI-Enabled analytics while contributing to an integrated solution that connects validation and production data sources. The project focuses on creating a centralized dashboard capable of linking information from multiple databases and engineering tools to identify test coverage gaps, improve traceability, and generate actionable insights. The intern will also explore the application of Agentic AI solutions to enhance data interpretation and engineering decision-making.

Objective of the Project

Develop a scalable platform that consolidates component validation data from multiple sources into a unified view. Improve visibility of validation test coverage and potential coverage gaps across HBM products. Enable efficient data exploration and traceability through interactive analytics and visualization. Investigate AI-Enabled approaches, including Agentic AI capabilities, to generate insights and recommendations from engineering data.

Opportunities for Full Time Employment

This internship offers exposure to advanced semiconductor product validation, data analytics, and AI-driven engineering solutions. High-performing interns may be considered for future full-time opportunities, subject to business needs and hiring requirements.

Project Scope

Design and develop a web-based dashboard capable of querying and visualizing data from multiple engineering databases, including validation and production data sources. Develop data models and relational database structures to enable scalable and efficient data integration. Establish connections with existing Component Validation dashboards to provide improved data accessibility and traceability. Implement event-based notification mechanisms that highlight predefined validation or test coverage conditions. Explore the integration of Agentic AI capabilities to generate contextual insights and streamline engineering data analysis.

Learning Opportunities

Gain practical experience in full-stack dashboard development and data engineering within a semiconductor product development environment. Learn database design principles, data integration methodologies, and scalable analytics architecture. Apply modern data visualization practices to communicate complex engineering information effectively. Explore AI-Enabled workflows, including the use of Generative AI, AI Assistants, and Agentic AI technologies for data-driven decision-making. Collaborate with engineering professionals involved in HBM product validation and system engineering.

Deliverables

• A scalable, interactive, and user-friendly dashboard for HBM Component Validation Development analytics.
• Integrated data infrastructure that enables efficient retrieval, linkage, and visualization of validation-related information.
• Automated notification functionality for user-defined validation and coverage events.
• AI-Enabled analytics features that provide engineering insights and highlight potential test coverage gaps.
• Documentation covering system architecture, data design, and dashboard functionality.

Impact of the Project

• Enhance visibility into validation development activities and test coverage status.
• Improve engineering efficiency through centralized access to relevant validation and production data.
• Enable data-driven decision-making through interactive visualization and analytics.
• Strengthen traceability between validation activities and product development outcomes.
• Demonstrate the value of Agentic AI solutions in semiconductor engineering workflows.

Skillsets Required

• Familiarity with Agentic AI tools, Generative AI platforms, or AI-Enabled engineering workflows.
• Programming experience in Python and/or Java for data processing, automation, and system integration.
• Experience with Tableau or similar data visualization platforms.
• Understanding of database concepts, SQL, and relational data modeling.
• Basic knowledge of data analytics and visualization best practices.

Course of Interest

The ideal candidate should be pursuing a Bachelor's or Master's degree in Computer Engineering, Electrical and Electronic Engineering, Computer Science, Data Science, or a related field.

Duration of Period

The ideal candidate should be able to commit to a full time internship period of at least 3 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.

To learn more, please visit micron.com/careers

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.