Internship - AI for Knowledge Management & Decision Support

CMA CGM; Marseille; Sur place; EUR 12 000 - 19 000; Temps partiel

Résumé du poste

CMA CGM Fleet Center invites engineering or data science students to join as an AI-driven knowledge management intern in Marseille. You will document the Dynamic Routing ecosystem, build a knowledge base, and design governance for automated updates, while interfacing with AI agents and routing models.

You will collaborate with IT, R&D, and Fleet Center teams to translate complex routing decisions into explainable documentation and reports, contributing to real-time decision support in maritime

Qualifications

• Currently an Engineering or Master's student in Data Science, AI, CS or Applied Mathematics (in progress).
• Strong Python and data processing experience.
• Able to document, communicate and analyse complex systems.

Responsabilités

• Document the Dynamic Routing ecosystem and centralize knowledge from multiple sources.
• Create an inventory of information: data sources, ownership, dependencies and update processes.
• Build a structured, searchable knowledge base for Fleet Center, IT and R&D teams.
• Define governance and automated update mechanisms for the documentation.
• Design an AI agent prototype to explain models, constraints and limitations of routing decisions.
• Develop automated generation of explanatory route reports and knowledge sheets.
• Explain routing recommendations, assumptions and known limitations.
• Support teams in understanding routing decisions.

Connaissances

Python

Data processing

Analytical skills

Documentation skills

Communication skills

Formation

Engineering or Master's student

Description du poste

CMA CGM Fleet Center manages large-scale vessel routing operations, relying on multiple data sources, optimization tools, vessel performance models, operational constraints and business rules. Key knowledge is currently distributed across systems, experts, documents and databases.

You will join the Fleet Center, IT and R&D teams to develop an AI-powered solution that improves the documentation, transparency and traceability of routing decisions, covering the full Dynamic Routing ecosystem: weather data providers and forecasting models, optimization engines and routing algorithms, vessel performance models (digital twins), operational constraints and business rules, geospatial reference databases (bathymetry, Traffic Separation Schemes, environmental or regulatory zones), as well as the internal Dynamic Routing, RDT and MyRoute tools.

It is an opportunity to work on a high-impact operational use case at the intersection of generative AI, maritime routing, knowledge management and decision support.

WHAT ARE YOU GOING TO DO?

• Document the Dynamic Routing ecosystem and centralize knowledge from multiple sources.
• Build a comprehensive inventory of the information requiring documentation: data sources, ownership, dependencies and update processes.
• Build a structured, searchable and maintainable knowledge base, usable by the Fleet Center, IT and R&D teams.
• Define the governance and automated update mechanisms for the documentation.
• Design an AI agent prototype able to answer questions about the models used, the constraints considered and the known limitations of a routing recommendation.
• Develop automated generation of explanatory route reports and knowledge sheets (assumptions, models, constraints, data sources, known limitations).
• Explain routing recommendations, calculation assumptions and known limitations.
• Support the Fleet Center, IT and R&D teams in understanding routing decisions.

WHO ARE WE LOOKING FOR?

• Education: Engineering or Master's student in Data Science, Artificial Intelligence, Computer Science or Applied Mathematics, currently in progress
• Experience: with Python and data processing
• Skills: strong analytical, documentation and communication skills
• Adaptability: ability to understand complex technical systems and collaborate with multidisciplinary teams
• Strong interest in Generative AI, knowledge management and decision-support systems
• Knowledge of LLMs, RAG architectures, vector databases, knowledge graphs or AI agents
• Interest in maritime transportation, operations and optimization