Intern - Assembly Post Electrical

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 20,000 - 33,000; Full time

Job summary

Micron Technology, Inc. invites applications for an internship focused on Intelligent Equipment Health Monitoring and Reliability Analytics. You will work on data analytics, ML models, and AI-enabled dashboards to monitor equipment health, detect abnormal behavior, and communicate insights to engineering teams.

The role offers exposure to Python, SQL, data visualization, and AI techniques, with opportunities for future full-time employment subject to business needs.

Qualifications

• Pursuing a degree in Data Analytics, Data Science, CS, Mechanical/Electrical/Industrial Engineering or related field.
• Proficiency in Python and SQL; strong data analytics and visualization skills.
• Familiarity with ML, AI, anomaly detection, and data science concepts.
• Strong analytical, problem-solving, and technical communication skills.
• Ability to convey insights to engineering stakeholders.

Responsibilities

• Develop a prototype Intelligent Equipment Health Monitoring Agent and interactive dashboard.
• Analyze alarms, downtime, maintenance, and performance data to identify health trends.
• Apply statistical and ML techniques to detect abnormal behavior and emerging concerns.
• Document methodology, findings, limitations, and recommendations for stakeholders.
• Communicate insights through dashboards and analytical summaries.

Skills

Python

SQL

Data analytics

Statistics

Data visualization

Machine learning

AI concepts

Anomaly detection

Technical communication

Education

Data Analytics degree

Data Science degree

Computer Science degree

Electrical/Mechanical/Industrial Engineering degree

Tools

Python tools

SQL

Jupyter

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.

Project Title

Intelligent Equipment Health Monitoring and Reliability Analytics Using Artificial Intelligence

Project Description

This project provides the intern with practical exposure to manufacturing equipment reliability, data analytics, machine learning, Artificial Intelligence, and engineering visualization. The intern will develop a prototype that analyzes equipment alarms, downtime, maintenance, and performance data to identify equipment health trends and emerging reliability concerns. The intern will also explore AI-Enabled and natural language capabilities for communicating analytical insights to engineering stakeholders.

Objective of the Project

• Monitors equipment health and reliability trends.
• Detects abnormal equipment behavior and emerging concerns.
• Identifies when performance degradation began.
• Highlights the main factors associated with degradation.
• Communicates findings through dashboards and analytical summaries.

Opportunities for Full Time Employment

Consideration for future internship or full-time employment opportunities will be subject to business needs, position availability, and the applicable selection process.

Project Scope

• Analyze equipment alarm history, downtime records, maintenance activities, and operational performance data.
• Develop equipment health indicators and monitoring methodologies to evaluate reliability trends.
• Apply statistical and machine learning techniques to identify abnormal equipment behavior and emerging reliability concerns.
• Develop an Intelligent Equipment Health Monitoring Agent and interactive dashboard to communicate trends and key contributors.
• Document and present the methodology, findings, limitations, and recommendations to engineering stakeholders.

Learning Opportunities

• Gain practical experience in manufacturing data analytics and equipment reliability engineering.
• Apply data preparation, trend analysis, anomaly detection, and machine learning techniques.
• Learn to develop equipment health indicators and evaluate their effectiveness.
• Explore AI-Enabled Agents and natural language capabilities for engineering analytics.
• Strengthen technical documentation, visualization, problem-solving, and presentation skills.

Deliverables

• A prototype of an Intelligent Equipment Health Monitoring Agent.
• A documented equipment health scoring methodology and set of reliability indicators.
• Automated models for detecting alarm spikes, downtime excursions, and equipment health degradation.
• An interactive dashboard showing equipment health trends, abnormal trend start points, and key contributors.
• A final technical report and presentation covering findings, limitations, recommendations, and future opportunities.

Impact of the Project

• Improve visibility into equipment health and reliability trends.
• Enable faster identification of potential contributors to downtime and alarm excursions.
• Improve early detection of emerging equipment reliability concerns.
• Provide data-driven insights for proactive reliability improvement.
• Establish a scalable AI-Enabled analytics framework for future development.

Skillsets Required

• Programming knowledge in Python, Structured Query Language, or equivalent analytical tools.
• Understanding of data analytics, statistics, trend analysis, and data visualization.
• Familiarity with machine learning, Artificial Intelligence, anomaly detection, or data science concepts.
• Familiarity with AI tools, AI-Enabled workflows, Generative AI, or Agent-based analytics.
• Strong analytical, problem-solving, technical communication, and documentation skills.

Course of Interest

The ideal candidate should be pursuing a degree in Data Analytics, Data Science, Computer Science, Mechanical Engineering, Electrical Engineering, Industrial Engineering, or a related field.

Duration of Period

The ideal candidate should be able to commit to a full time internship period of at least 5 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.