AI Engineer – Internship

🕒 4 days ago

🇫🇷 France – Remote

👨‍🎓 Internship

⚪️ Entry-level

🤖 AI Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Capgemini

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1967

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Capgemini is a global leader in partnering with businesses to transform and manage their operations by harnessing the power of technology. With expertise across a wide array of industries such as aerospace, automotive, banking, and healthcare, Capgemini provides a constantly evolving portfolio of services to meet the ever-changing needs of their clients. Their offerings include cloud, cybersecurity, data and artificial intelligence, and enterprise management, among others. Capgemini also emphasizes innovation and sustainability, helping companies achieve digital transformation while promoting environmental and social responsibility. Additionally, Capgemini provides career opportunities across various levels and professions, encouraging innovation and diversity in its workforce.

📋 Description

• Join the SogetiLabs R&D team, composed of researchers and AI experts • Develop an explainable artificial intelligence (XAI) framework for vehicle-to-everything (V2X) communications • Work on XAI-based automation in software-defined networks (SDN) • Become familiar with the SDN + Contiki/Cooja platform and set up a V2X network scenario • Define and implement several V2X application profiles generating distinct traffic patterns • Develop a flow-based packet collection and aggregation module in the SDN controller • Extract temporal and statistical features and export annotated traces • Design a network-token sequence encoding and train a GNN model • Compare performance with Random Forest or XGBoost models • Integrate the model into the controller through an inference service, such as a REST API • Implement explainable AI techniques, including attention analysis, feature importance, Chain-of-Thought (CoT), and counterfactual explanations • Experimentally evaluate the quality of classification and explanations across different scenarios

🎯 Requirements

• Master’s degree in Telecommunications or final-year engineering degree with a focus on telecommunications • Seeking a final-year internship • Strong knowledge of networking (TCP/IP model, fundamentals of IoT/WSN, V2X, and SDN) • Proficiency in Python for data processing and machine learning • Knowledge of PyTorch, TensorFlow, or an equivalent framework • Knowledge of machine learning (supervised classification, training/validation, and introductory deep learning) • Comfortable working in a Linux environment (command line, Git, etc.) • Basic knowledge of Java • Good written and spoken English (minimum B2 level) • Fluent French (minimum C1 level) • Scientific rigor, adaptability to change, initiative, and teamwork • Experience with Contiki/Cooja or sensor networks is a plus • Interest in explainable AI (XAI) and topics at the intersection of networking and AI is a plus • Familiarity with LLMs is a plus

🏖️ Benefits

• Training programs, including boot camps • Certifications (Azure, Databricks, Scrum, etc.) • Immersive programs such as the GenAI Campus • Opportunities to work remotely from France and internationally • Health and well-being support (support helpline, dedicated platform, etc.) • Inclusive networks and environment (Women@Capgemini, Parents@Capgemini, OUTfront, CapAbility) • EDGE+-certified workplace recognized by the Bloomberg Gender Equality Index • Happy Trainees commitment for interns and apprentices • Multicultural and disability-inclusive workplace • Community initiatives and commitment to reducing environmental impact