Freelancer profile translated to English.

Description

Do you want to integrateartificial intelligence (AI)into your business processes?

Is your machine learning prototype struggling to go into production?

Do you want to design and deploy a complete application integrating AI?

With over 10 years of experience in AI,Machine Learning (ML)withPython— including a PhD in AI and over 5 years in industry — I help companies design, deploy, and maintain AI systems tailored to their real needs.

My expertise:

*Machine Learning & Generative AI:Integration and optimization of NLP, LLM, GenAI models and custom business process automation.

*Full Stack Web Development:Creation of robust, scalable, and modular applications with Django, React, FastAPI, and Tailwind CSS, seamlessly integrating AI.

*MLOps & Industrialization:Implementation of reliable, scalable, and maintainable MLpipelines— including feature stores, model registries, orchestrators, and metadata stores — CI/CD, continuous model training (CT), monitoring, and complete model lifecycle management.

I work across the entire AI project lifecycle, from technical definition to production, including cloud architecture (**AWS**, DigitalOcean) and, if necessary, team coordination. I have notably integrated solutions likeRetrieval-Augmented Generation (RAG)andagentswithLangChainand **LangGraph**.

I am dedicated to transforming your AI projects into concrete competitive advantages, by automating your operations while ensuring scalability and maintainability.

To discuss your needs and discover how I can assist you, contact me.

Languages

French
Native or bilingual
English
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km)

Informatique CDC
AI/Machine Learning Engineer
September 2025 - Today (11 months)
Bagneux, France
Situation:The company wanted to develop an internal chatbot to
accompany and automate certain business tasks.

Task:Design, develop, and optimize chatbot functionalities.

Actions:
Implemented a multi-format data extraction feature (PDF and Docx) with LangChain.
Developed a multilingual document translation feature via Azure.
Improved LLM system prompts and the logic of existing functionalities to increase response relevance.
Mentored collaborators, ensuring their skill development and the quality of deliverables.
Optimized GitLab CI/CD pipelines by applying MLOps best practices.
Documented algorithm design to facilitate knowledge sharing and ensure reproducibility.

Result:Reduced pipeline execution times by 50% and
increased internal user adoption of the chatbot.

Stack:Python, FastAPI, LangChain, LangGraph, Mistral API, OpenAI API, Hugging Face, Asyncio, Microsoft Azure, Docker, Pydantic, Pytest, Git, GitLab CI/CD, MongoDB, Beanie, JavaScript.
FastAPI Python Microsoft Azure LLM Langchain
Asyora
Full Stack Developer
August 2023 - June 2025 (1 year and 10 months)
Bagneux, France
Situation:Entrepreneurial initiative to launch a SaaS solution aimed at reducing time spent in traditional meetings.

Task:Design an asynchronous meeting platform integrating best practices to optimize time management.

Actions:
Full development of the solution with Django (Python), Htmx, and Tailwind CSS.
Deployment and management of infrastructure on Amazon Web Service (AWS) and DigitalOcean.
PostgreSQL database management.
Application of DevOps best practices such as CI/CD and testing (unit, integration, and system).
Documented algorithm design to facilitate knowledge sharing and ensure reproducibility.

Result:Notable reduction in the number and duration of meetings, with a significant improvement in user productivity.

Stack:Python, Django, Amazon Web Service, Docker, Pytest, Tailwind CSS, Htmx, DigitalOcean, Git, Github Actions CI/CD, PostgreSQL, JavaScript.
Django Python Amazon Web Services DevOps Fullstack
Groupe Rhapsodie
Machine Learning Engineer
October 2021 - August 2024 (2 years and 10 months)
Paris, France
Situation:The company wanted to create an artificial intelligence (AI) laboratory dedicated to developing solutions specializing in emotion recognition from text (NLP) and speech.

Task:Design a robust, scalable infrastructure aligned with the company's vision, while implementing state-of-the-art machine learning models for specific applications.

Actions:
Set up infrastructure applying MLOps best practices.
Data collection, transformation, and annotation.
Development and deployment of deep learning models (PyTorch).
Integration and adaptation of large language models (LLMs).
Creation of intelligent agent prototypes with LangGraph and LangChain.
Management and optimization of computing resources.
Mentored collaborators to ensure development consistency.
Documented algorithm design to facilitate knowledge sharing and ensure reproducibility.

Result:Implementation of an operational laboratory with an optimized MLOps workflow, enabling rapid deployment of AI products.

Stack:Python, Hugging Face, OpenAI API, LangChain, LangGraph, ZenML, PyTorch, Gradio, MLflow, Qdrant, Git, Github Actions CI/CD, Amazon Web Service (AWS), NumPy, Pandas, Pytest, Seaborn, Asyncio, Docker, Django, FastAPI, Tailwind CSS, Htmx, JavaScript.
artificial intelligence Python LLM LangGraph MLOps