
AI Engineer with 2+ years in NLP & LLM
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Assessing your cultural and operational fit
Ingénieur IA spécialisé en NLP et modèles de langage (LLM), je conçois des systèmes d'IA appliquée de bout en bout: architecture RAG, fine-tuning, évaluation rigoureuse et déploiement en production. Mon expérience couvre la mise en œuvre de solutions en environnement à fortes contraintes (privacy, fiabilité, domaines spécialisés) - des compétences transférables à tout secteur où le NLP/LLM doit être robuste et explicable. À la recherche d'un CDI pour construire des systèmes d'IA à fort impact.
Avignon Université
Master 2 · Intelligence Artificielle
October 1, 2024 – August 1, 2026
Università degli Studi di Ferrara
Licence · Informatique
January 1, 2021 – December 1, 2023
Institut du Cancer Avignon-Provence (ICAP)
Ingénieur IA & NLP - Stage de fin d'études
February 1, 2026 – Present
Avignon, Provence-Alpes-Côte d'Azur, France
Laboratoire d'Informatique d'Avignon (LIA)
Ingénieur IA - Projet NLP (Transcription sténogrammes)
February 1, 2025 – June 1, 2025
Avignon, Provence-Alpes-Côte d'Azur, France
Avignon Université
Ingénieur IA - Assistant vocal conversationnel (Robot Pepper)
October 1, 2024 – January 1, 2026
Avignon, Provence-Alpes-Côte d'Azur, France
Betacom Group
Développeur Full-Stack
May 1, 2024 – October 1, 2024
Italy
Cultural Fit Analysis
The candidate's project diversity, ranging from medical NLP to conversational AI and e-commerce, demonstrates a broad applicability of their skills. Their academic background in AI and practical experience in various AI/NLP roles align perfectly with the target role of an AI Engineer. The emphasis on robust, explainable, and privacy-conscious AI systems indicates a strong cultural fit for organizations prioritizing ethical and responsible AI development.
Soft Skills & Operational Fit
The candidate exhibits strong scientific rigor, initiative, and adaptability, which are critical for an AI Engineer role. Their experience in interdisciplinary work suggests good collaboration skills. The focus on privacy-first deployment and rigorous evaluation aligns well with best practices in operationalizing AI systems.