Freelancer profile translated to English.
Back to original languageAbout Louis
Senior AI Engineer & Data Scientist (7 years of experience) passionate about complex technical challenges. Expert in Python, GenAI (LLM, RAG, Multi-Agents) and MLOps. I combine a product approach (DDD/Lean) with technical rigor acquired in MedTech and Cybersecurity. Based in Paris.
French
Native or bilingual
Can work on-site
Paris (up to 50km)
Experience
- QantumLead AI EngineerDIGITAL AND ITJune 2025 - Today (1 year)Paris, FranceContext: Development of accounting software based on a Multi-Agent architecture to automate the entry of accounting records from PDFs.Responsibilities:- Project bootstrap and definition of technical architecture (Domain Driven Design approach).- Redesign of the initial prototype: transition from simple scripts to a finite state machine for increased robustness.- Development of AI agents (extraction, classification) and the API.- Implementation of the evaluation module (LLM as a Judge, NLP metrics) to measure performance and prevent regressions.- Monitoring of costs and errors in production.Stack: Python, FastAPI, GCP (Vertex AI), Gemini, Anthropic, Docker.
- Maki PeopleSenior Data Scientist & LLM Ops EngineerHUMAN RESOURCESFebruary 2025 - June 2025 (4 months)Paris, FranceContext: Design of a Voicebot to automate HR pre-qualification interviews over the phone.Responsibilities:- Redesign of the multi-agent system architecture to handle real-time voice flow.- Setup of the testing environment: generation of synthetic conversations (LLM vs LLM) to validate scenarios without real calls.- Implementation of comprehensive monitoring (latency, response quality) via Langfuse.- Development of connectors and business logic.Stack: Python, GCP, Vertex AI, Langfuse, vLLM, RunPod, Llama, Gemini.
- EvrygHead of GenAIDIGITAL AND ITOctober 2024 - February 2025 (4 months)Paris, FranceContext: Leading Data/AI expertise within a consulting firm and technical delivery for clients.Responsibilities:- Development and industrialization of RAG (Retrieval Augmented Generation) solutions: customization of chunking, integration of LanceDB and re-ranking.- Creation of a constraint-based matching tool for an NGO (using linear optimization/Simplex rather than LLM to ensure reliability).Stack: Python, Vertex AI, LanceDB, RAGAS, Docker.
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Education
- Associate s Degree in Computer Software EngineeringCentrale Lille2018Master's degree, Software Engineering et Machine Learning