About Thibault
👋 Welcome
You know AI could help your business. The hard part is building it right, and making sure it keeps working six months down the line.
I'm a Machine Learning Engineer specializing in production AI systems, from data pipelines to ML models to LLM integration.
Since 2020, I've been turning prototypes into systems that run in the real world, at scale, and over the long term.
Prediction models, fraud detection, categorization engines, AI agents.
I've seen what works, and more importantly, what doesn't.
🎯 What I Build
💎 Prediction & forecasting models aligned with your actual business goals.No hype, just systems that solve real problems and move real numbers.
🛡️ Production-grade ML pipelines with automated monitoring. Your models stay accurate over time, not just on launch day.
💰 Cloud architectures on GCP, AWS, and Azure calibrated to handle high loads without skyrocketing costs.
🤖 LLM integration and AI agents built into your existing products. Not standalone demos, but features that actually ship.
📉 Long-term reliability through continuous monitoring and automated retraining. Your AI doesn't expire.
🏆 What Makes Me Different
🤝 I don't just know ML. I bring strong software engineering practices to every project, which means scalable, maintainable, documented code your team can actually own.
🚀 Zero over-engineering. Every line of code has a purpose, and the simplest solution that works is always the right one.
🔑 Full transparency. You always know what's being built, why it's being built, and how it performs.
Ready to ship AI that actually works? Let's talk.
French
Native or bilingual
English
Native or bilingual
Remote only
Primarily works remotely
Experience
- OppiziMachine Learning EngineerFebruary 2025 - February 2026 (1 year)Transforming experimental city-level models into a global, real-time production system and automating creative workflows with GenAI.Key Achievements:🚀 Built the "AI Roster" Engine: Led the end-to-end engineering of a core mission-generation system, transforming experimental city-level models into a global production asset.🌍 Global Predictive Modeling: Built and deployed conversion rate models at a global scale, integrating complex weather & geospatial datasets to maximize prediction accuracy.⚙️ Industrial MLOps & Architecture: Designed robust pipelines using Airflow, dbt, and SageMaker. Built high-performance FastAPI services to handle real-time mission generation and inference under load.🤖 GenAI & Process Automation: Developed LLM-based agents to automate artwork workflows. Successfully deployed agents for flyer generation, classification, and analysis, significantly reducing manual operational overhead.💻 Tech Stack: Python, PyTorch, AWS SageMaker, FastAPI, Airflow, dbt, LLMs.
- YounitedMachine Learning EngineerJanuary 2022 - January 2025 (3 years)Building the MLOps Backbone & Standardizing Workflows. Focused on increasing team velocity by building shared tooling and exploring early GenAI capabilities.Key Achievements:🛠️ MLOps Framework & Standardization: Architected an internal MLOps framework and Python project templates to standardize development. Implemented reproducibility workflows (using DVC & CI/CD) to eliminate "it works on my machine" issues.🧠 GenAI & R&D Initiatives: Pioneered early RAG prototypes for internal knowledge retrieval. Contributed to advanced analytics workflows including embedding-based transaction clustering and LLM-assisted classification.🚀 Production & Observability: Deployed robust ML APIs and set up comprehensive monitoring dashboards to track model health in production.🤝 Leadership & Strategy: Mentored junior Data Scientists on engineering best practices and actively contributed to the technical roadmap planning.💻 Tech Stack: Python, DVC, CI/CD, LLMs, RAG, Embeddings, Docker.
- FinfrogData scientist - MLEFebruary 2020 - February 2022 (2 years)Paris, FranceCore Credit Scoring & Transaction Intelligence. Focused on enhancing risk assessment accuracy through Deep Learning and reliable API deployment.Key Achievements:💳 Advanced Credit Scoring Built and optimized core credit scoring models, directly contributing to more accurate risk assessment and underwriting decisions.🧠 Deep Learning for Transactions Developed Neural Networks to analyze complex transaction patterns, unlocking deeper behavioral insights beyond traditional scoring.⚡ Real-Time Underwriting APIs Designed and maintained high-availability Scoring APIs, serving as the backbone for immediate underwriting decisions.💻 Tech Stack: Python, Scikit-learn, TensorFlow/Keras, Flask/FastAPI, SQL.
Reviews
Nathan
CTO Eklypse Studio - Eklypse studio
Reviewed on 13/02/2026
Working with Thibault was an eye-opener. They didn't just run a standard checklist, they really dug into our architecture and found specific edge-cases that our internal team had become 'blind' to. The final report was refreshing: no academic fluff, just a clear, prioritized list of risks and exactly how to fix them. If you want a sanity check on your AI that actually goes deep, this is the person to hire.
Erwan
Co-Fondateur SkyVision - SKYVISION
Reviewed on 05/02/2026
Before hiring Thibault, we were wasting time and money trying to get our AI systems to run smoothly. He came in, quickly identified the issues, and built a solution that saved us hours of manual work every week.
Thibault is fast, efficient, and incredibly easy to work with. He focuses on results and getting the job done right the first time. If you want your AI project completed without the headaches, he is your guy.
Recommendations
+1
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Education
- Engineer's degreeUniversité de Technologie de Compiègne2020Specialization: Data Mining & Machine Learning
Certifications
- Professional Cloud Developer CertificationGoogle2024