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Cléophas F.CF

Cléophas F.

AI/ML Engineer · RAG & Multi-Agent Architect

€600/day
Paris, FR
0-2 years

Average response time: 1 hour

About Cléophas

Specializations
  • Designing modern, secure RAG architectures (guardrails, rewriting, HyDE, reranking)
  • Building advanced AI agents (LangChain, LangGraph, function/tool calling)
  • End-to-end monitoring of these systems (ElasticSearch, LangSmith, DeepEval).

Background


Graduated with a Master’s degree in Data Science (Big Data & AI) from EFREI Paris.

Professional Experience


I have worked with large organizations such as RATP and Crédit Agricole (CASA).
  • Environments: Data, Machine Learning, Generative AI, AWS
  • Methodologies: Agile / Sprint-based development
  • Cloud Certifications: Azure Fundamentals, AWS Cloud Practitioner

Key Missions & Projects

  • Optimized an existing RAG system, improving performance through chunking strategies, prompt engineering, and query rewriting
  • Fine-tuned LLMs for a regression task
  • Implemented LLM compression techniques, including quantization, pruning, and knowledge distillation
  • Built an automated data-quality monitoring system using Python, ELK, and Airflow
  • Designed 12 Python optimization rules, reducing Data Science and Deep Learning workflow runtimes by up to 50%. Contribution to the Creedengo-Python GitHub project
Core Skills


LLM/RAG, AI Agents, LangChain, LangGraph, LangSmith, DeepAgents, Hugging Face, Python, PyTest, Scikit-Learn, Airflow, ELK, NextJS, PostgreSQL, DeepEval

Open to opportunities as a Machine Learning Engineer, Data Scientist, or Data & AI Engineer.
  • English

    Native or bilingual

  • French

    Native or bilingual

Can work on-site
Paris (up to 50km)

Experience

  • Crédit Agricole SA Data Lab Groupe
    Data Scientist/AI engineer
    BANKING AND INSURANCE
    March 2025 - September 2025 (6 months)
    Montrouge, France
    Développement de 12 règles d'optimisation Python (standards de qualité de code)
    Modification de l'orchestrateur RAG pour intégrer un suivi en temps réel de l'impact environnemental
    Développement de tests unitaires (pytest) pour valider les fonctionnalités intégrées à l'orchestrateur
    Entraînement de modèles de prédiction des coûts IA (XGBoost et finetuned ModernBERT)
    Stack : PyTorch AWS Bedrock FastAPI pytest CUDA Poetry/uv
    Python Pytorch FastAPI Amazon Web Services Pandas
  • Kadom SAS - Deviens Superhote
    Fullstack developer
    DIGITAL AND IT
    October 2024 - November 2024 (1 month)
    Rimini, RN, Italy
    Développement d'une Progressive Web App (PWA) avec React et le framework Next.js
    Mise en place de workflows automatisés avec Make, interagissant avec l'API de l application
    Configuration d'une pipeline CI/CD automatisée avec GitHub et Vercel
    Stack : Next JS CI/CD TypeScript REST API GitHub Git PostgreSQL
    Typescript Next.js CI/CD Management Make.com PostgreSQL
  • CITiO
    Data engineer
    TRANSPORTATION
    November 2023 - April 2024 (5 months)
    Paris, France
    Conception et dé ploiement d'un système de suivi de KPI réduisant les incidents de qualité de données grâce à la mise en place d'alertes en temps réel sur les anomalies des pipelines
    Modification des pipelines de données pour répondre à l'évolution des besoins clients
    Stack : Python Pandas Airflow YAML Django
    Python Pandas KPIs and Metric Definition and Monitoring Data Pipelines and Warehousing

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Education

  • Master
    EFREI Paris Panthéon-Assas
    2025
    Ingénieur spécialisé en Big Data et Intelligence Artificielle

Certifications

Skill set

Categories