Ml & Platform Agentic Apprentice H/F

Description

Les missions du poste Led by Rodolphe Saadé, the CMA CGM Group, a global leader in shipping and logistics, serves more than 420 ports around the world on five continents. With its subsidiary CEVA Logistics, a world leader in logistics, and its air freight division CMA CGM AIR CARGO, the CMA CGM Group is continually innovating to offer its customers a complete and increasingly efficient range of new shipping, land, air and logistics solutions. Committed to the energy transition in shipping, and a pioneer in the use of alternative fuels, the CMA CGM Group has set a target to become Net Zero Carbon by 2050. Through the CMA CGM Foundation, the Group acts in humanitarian crises that require an emergency response by mobilizing the Group's shipping and logistics expertise to bring humanitarian supplies around the world. Present in 160 countries through its network of more than 400 offices and 750 warehouses, the Group employs more than 155,000 people worldwide, including 4,000 in Marseilles where its head office is located. YOUR ROLE At the heart of the Group Data Science team - you will help design, build, and evaluate AIdriven solutions in an environment where agentic (LLM and tooldriven) systems are increasingly used to automate and augment analytical workflows. Working closely with data scientists, data engineers, and platform teams, you will support tasks such as data exploration, feature engineering, model experimentation, and result interpretation, while also contributing to the design and testing of AI agents that assist with these activities. You will gain handson experience with ML and data tools, agentic workflows, and help ensure that insights and models are reliable, explainable, and usable by stakeholders across the organization. WHAT WILL YOU DO? As a Machine Learning & Data Science/ Agentic Platform Engineer apprentice, your responsibilities are as follows: - Perform data exploration of internal and external data ( identify relevant sources, cleaning of da