Data Transformation/Digital Systems Engineering InternSaint-Gobain

Saint-Gobain est présent dans 70 pays avec plus de 170 000 collaborateurs. Le Groupe mobilise les savoir-faire de ses sociétés et propose une offre de solutions pour des bâtiments confortables, plus économes en énergie et plus agréables à vivre au quotidien. Il positionne également ses matériaux de haute performance sur les marchés industriels et de consommation tels que l'automobile, l'aéronautique, la santé ou l'énergie.

Job Summary

The Data Transformation / Digital Systems Engineering Intern will support digital and AI-enabled solutions for Engineering, Quality, and Production at the Beaverton site. The primary assignment is to work with approved, controlled documents to develop data rules, metadata, document relationships, retrieval logic, and process workflows for an AI Retrieval-Augmented Generation (RAG) knowledge system.

The intern will help test AI-generated results against approved source documents and document requirements, workflows, findings, and recommended improvements. The role will also provide exposure to GitHub, Microsoft Copilot, Ignition, QAD, PLCs, and manufacturing data systems.

In this role, you will:

• Review and organize controlled engineering, quality, and production documents.
• Develop rules, metadata, document relationships, and retrieval logic for the AI/RAG system.
• Create process workflows for document retrieval, review, approval, and use.
• Develop and test Python or similar scripts supporting data transformation and automation.
• Test AI/RAG responses against approved source documents and identify improvement opportunities.
• Support digital-system work involving GitHub, Microsoft Copilot, Ignition, QAD, PLCs, and manufacturing data.
• Collaborate with Engineering, Quality, Production, and digital/IT resources.

Required Qualifications:

Currently pursuing a bachelor's degree in Computer Science, Information Technology, Software Engineering, or other related disciplines.

• Generative AI, programming, digital systems, data transformation, and process workflow development.

• Programming through school projects, coursework, engineering teams, competitions, internships, or personal projects.

• Demonstrated Python or similar programming experience.

• GitHub, Microsoft Copilot, RAG, data structures, databases, Ignition, SCADA/MES, QAD/ERP, PLCs, automation, or process mapping.

• Prior internship experience is beneficial but not required.

• Problem solving, analytical thinking, attention to detail, documentation, communication, teamwork, and willingness to learn.