AI for Manufacturing Excellence Intern

BD; Singapore; On-site; SGD 20,000 - 28,000; Full time

Job summary

BD is seeking a full-time six-month AI solutions internship in Singapore. You will design and develop AI assistants on governed enterprise platforms, ensuring data governance, traceability, and confidence in outputs.

You will build prompts, workflows, and retrieval logic, while maintaining test sets and safeguards. The role focuses on identifying productivity improvements across plants, linking losses to cost drivers, and organizing a reusable prompt library for manufacturing excellence.

Qualifications

• Pursuing a degree in Engineering, Industrial Engineering, Data Science, Computer Science, Information Technology, Business Analytics or a related field.
• Available for a full-time six-month internship.
• Practical exposure to Python or Power Platform and basic SQL.
• Interest in AI, manufacturing, operational excellence and business improvement.
• Willingness to travel to Tuas Avenue 2 manufacturing sites when required; primary work location at Jurong East.

Responsibilities

• Design and develop an AI assistant using approved enterprise platforms.
• Build solutions on approved data layers with proper data governance.
• Develop prompts, workflows and retrieval logic with traceable sources.
• Create safeguards and citations for outputs.
• Develop and maintain a structured test set for plant questions and access controls.

Skills

Python

Power Platform

SQL

AI interest

Willingness to travel

Education

Engineering/Industrial Engineering/Data Science/CS/IT/Business Analytics (pursuing)

Tools

Microsoft Copilot Studio

Azure AI Foundry

Power BI

Job description

BD is seeking a full-time six-month AI solutions internship in Singapore. You will design and develop AI assistants on governed enterprise platforms, ensuring data governance, traceability, and confidence in outputs.

You will build prompts, workflows, and retrieval logic, while maintaining test sets and safeguards. The role focuses on identifying productivity improvements across plants, linking losses to cost drivers, and organizing a reusable prompt library for manufacturing excellence.