AI-Enabled Facilities Intern — Predictive Analytics

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

Job summary

Micron Technology, Inc. Singapore invites interns to explore AI, ML, data analytics, automation, and digital technologies within a semiconductor facilities environment.

You will work on AI-enabled solutions to improve equipment reliability, predictive analytics, operational efficiency, and engineering knowledge access. The internship offers exposure to real industrial datasets, collaboration with Facilities engineers, and opportunities for future full-time roles based on performance.

Qualifications

• Basic understanding of AI, ML, data analytics, or statistics.
• Programming in Python and SQL.
• Familiarity with data visualization tools (Power BI, Tableau).
• Understanding of databases, data processing and software development principles.
• Curiosity to learn emerging technologies.

Responsibilities

• Analyse operational and sensor data to identify trends, anomalies, and optimization opportunities.
• Develop AI/ML prototypes for predictive maintenance and equipment monitoring.
• Create dashboards, visualization tools, or automation workflows for engineering decisions.
• Explore AI-enabled knowledge-management solutions to improve information accessibility.
• Collaborate with Facilities engineers and domain experts.

Skills

Python

SQL

Data analytics

Statistical concepts

Curiosity to learn

Education

Pursuing Degree in AI/Data Science/CS

Enrollment in related field

Tools

Power BI

Tableau

SQL databases

Job description

Micron Technology, Inc. Singapore invites interns to explore AI, ML, data analytics, automation, and digital technologies within a semiconductor facilities environment.

You will work on AI-enabled solutions to improve equipment reliability, predictive analytics, operational efficiency, and engineering knowledge access. The internship offers exposure to real industrial datasets, collaboration with Facilities engineers, and opportunities for future full-time roles based on performance.