Freelancer profile translated to English.
Back to original languageAbout Corentin
👋 Hello
Data Engineer & Data Scientistgraduated from INSA Lyon and Polytechnique Montréal, I have been assisting companies for over 7 years in deploying artificial intelligence systems in production.
I have led strategic projects as Lead Data & AI in over 30 organizations(Biomérieux, CEA, Proximus, Swile, Salomon, Verkor)to transform their challenges into operational solutions creating measurable value.
🎯 My Methodology
Strategic framing to identify high ROI use cases,field validationwith a prototype tested by your teams, thenindustrializationwith production architecture, monitoring, and training.
The objective: robust systems that your teams can adopt and maintain.
🔧 My Technical Expertise
My multiple experiences have allowed me to acquire end-to-end expertise:
- Data Engineering & Architecture: ETL Pipelines, structuring and integrating heterogeneous sources, governance, sovereignty, and data quality.
- ML, Deep Learning & LLM: Fine-tuning LLMs, machine learning, deep learning, advanced Data Science techniques (transfer learning, active learning, federated learning)
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- Generative AI Solutions: Chatbots, RAG,Knowledge graphs, AI agents, prompt engineering, and model optimization (LangChain, LangGraph, Neo4j, Qdrant)
- MLOps & Deployment: Production infrastructure (AWS, Azure, GCP, on-premise, hybrid), monitoring, drift detection, observability.
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- Agile Management: Coordination on progress and decisions with teams.
💡 My Approach
Pragmatism and transparency. If AI is not the best solution, I will tell you. My goal: to sustainably leverage your data through artificial intelligence systemsthat your teams can adopt.
✅ I am approved for **Innovation Tax Credit (CII)**: 30% tax credit on your projects
French
Native or bilingual
English
Native or bilingual
Remote only
Primarily works remotely
Experience
- ProximusAI Architect - Data & AI EngineerTELECOMMUNICATIONSJuly 2024 - Today (1 year and 11 months)Bruxelles, Belgium⛰️ ChallengesDevelopment of an AI chatbot to improve internal knowledge sharing.🎯 ObjectivesCreate a chatbot solution capable of accurately answering internal questions with a high level of contextual understanding, while ensuring the confidentiality and relevance of the responses.📚 Accomplishment⬥ Design of an innovative AI architecture based on the Agentic RAG paradigm.⬥ Implementation of a multi-agent system with a central orchestrator.⬥ Implementation of a ReAct approach to enhance agent reasoning.⬥ Development of an innovative data storage solution based on graphs rather than traditional vectors.⬥ Study of state-of-the-art Data Science, NLP, and Data Engineering concepts.⬥ Integration of the chatbot with various interfaces:
- Internal ticketing system
- Enterprise messaging (Slack, Teams)
- Web interface
💡 Key ResultsCreation of a chatbot capable of accurately answering internal questions.Development of a solution adaptable to an unstructured knowledge base.Significant improvement in information retrieval and sharing within the company. - bioMerieuxData Scientist - Data EngineerRESEARCHJune 2024 - December 2024 (6 months)Grenoble, France🎯 ObjectivesImprove the team's Machine Learning models by optimizing model hyperparameters.📚 AccomplishmentImplementation of state-of-the-art automatic hyperparameter optimization algorithms applied to Machine Learning algorithms.(Deep Learning Neural Networks, Gradient Boosting).Support for the Data Science team to enable the large-scale implementation of this solution.
- Move2 digitalData Engineer - LLMSOFTWARE PUBLISHINGJanuary 2024 - November 2024 (10 months)Lyon, France⛰️ ChallengesR&D to implement a state-of-the-art generative AI application for research and writing of research papers.🎯 ObjectivesAutomate data retrieval and the company's report writing process, while maintaining high data confidentiality.📚 Accomplishment⬥ Understanding business needs, data strategy, data engineering, data science, and project management.⬥ Selection of LLM models (proprietary or open-source): GPT-4 API or Mixtral 8x7B model.⬥ Implementation of vector and graph data models.⬥ Data preparation for fine-tuning and model adjustment (LoRA, QLoRA, DPO...).⬥ Setup of vector databases (Weaviate, Qdrant, Pinecone) and RAG.⬥ Creation of autonomous AI agents using LangChain and LangGraph.⬥ Design of a full-stack application using FastAPI and Next.js.
Reviews
Bruno
Move2.digital
Reviewed on 5/27/2024
Corentin is a good professional and has advanced knowledge in RAG AI, LLM finetuning. He manages his projects well.
E
Enrique
Enrique SOLA
Reviewed on 9/29/2022
Sincerely, a developer of formidable efficiency and reliability. Corentin intervened very quickly on our problem for a perfect result! I highly recommend him!
Recommendations
VD
HQ
+3
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Education
- Computer Engineering Degree, Data Science, Data Engineer, Machine LearningINSA Lyon - National Institute of Applied Sciences of LyonDiplôme d'ingénieur Informatique, Data Science, Data Engineer, Machine Learning
- Master Data Science, Data Engineer, Machine LearningPolytechnique MontréalSpécialisation Data Science & Data Engineering
Certifications
- CII ApprovalMinistry of Economy, Finance & Digital Sovereignty2023
- AI Booster ExpertBPI France2023