Intern, Facilities AI Engineering

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 Fab 10N Department Facilities Engineering, Artificial Intelligence and Smart Facilities Project Title Fab 10N Facilities Artificial Intelligence and Workflow Transformation Project Description This internship provides an opportunity to explore the application of Artificial Intelligence, Machine Learning, data analytics, automation, and digital technologies within a semiconductor manufacturing facilities environment. The project focuses on developing AI-Enabled solutions that enhance equipment reliability, predictive analytics capabilities, operational efficiency, knowledge accessibility, and engineering decision-making. The intern will gain exposure to real-world industrial datasets, engineering workflows, Artificial Intelligence technologies, and digital transformation initiatives. Through collaboration with Facilities engineers and domain experts, the intern will learn how advanced analytics and Artificial Intelligence can be applied to solve operational challenges and create business value. Objective of the Project Develop AI-Enabled solutions that improve Facilities Engineering analytics and decision-making. Apply Machine Learning and data analytics to equipment reliability, predictive maintenance, and operational data. Explore workflow-automation opportunities that improve engineering productivity and knowledge accessibility. Demonstrate the potential value of Artificial Intelligence within Smart Facilities initiatives.   Opportunities for Full Time Employment High-performing interns who demonstrate strong technical capability, learning agility, and successful project outcomes may be considered for future internship or full-time employment opportunities. Project Scope Analyse operational and sensor data to identify equipment trends, anomalies, and optimization opportunities. Develop Artificial Intelligence or Machine Learning prototypes for predictive maintenance and equipment monitoring. Create dashboards, visualization tools, or automation workflows that improve engineering decision-making. Explore AI-Enabled knowledge-management solutions that improve information accessibility and reuse.   Learning Opportunities Explore Artificial Intelligence and Machine Learning techniques for facilities equipment reliability and predictive maintenance. Learn how industrial data is collected, structured, governed, and used in Artificial Intelligence applications. Apply software-engineering principles to develop AI-Enabled tools, dashboards, and automation solutions. Gain exposure to Smart Facilities initiatives, including predictive analytics, robotics, and automation frameworks. Develop experience in Artificial Intelligence solution evaluation, validation, and continuous improvement.   Deliverables Artificial Intelligence prototypes or proof-of-concept solutions addressing selected facilities engineering challenges. Data analytics dashboards that provide actionable engineering insights. Predictive models or anomaly-detection solutions for facilities equipment monitoring. Structured knowledge repository or AI-Enabled knowledge-retrieval solution. Final documentation and presentation summarising the findings, recommendations, limitations, and potential business value.   Impact of the Project Improve visibility into facilities equipment performance and reliability. Enable earlier identification of equipment anomalies and potential performance issues. Enhance engineering decision-making through analytics, dashboards,