About Daniel
- Implementation of distributed, scalable, and orchestrated AI pipelines
- Deployment on Railway, Vercel, or your servers via Docker & GitHub CI/CD
- Automation of your business workflows with tools like n8n
- Integration of observability solutions like Langfuse or Dify.ai
- Comprehensive support: from proof of concept to production deployment
- Integration of LLMs into business products
- Intelligent automation of internal processes
- Deployment & monitoring of AI microservices
- Implementation of multi-step agentic workflows
French
Native or bilingual
English
Fluent
Chinese
Conversational
Experience
- Pretto,Industrialization and Optimization of LLM PipelinesREAL ESTATEDecember 2024 - May 2025 (5 months)Paris, France• Design & integration of Langfuse into a FastAPI API for observability, centralized management (prompts, datasets), and automated evaluation of LLM applications in production.• Optimization of LLM pipelines (inference costs divided by 20 across several PDF analysis cases).• Technological watch and PoC on automatic prompt optimization.• Detailed internship report: Link
- NETEASEAI Model Quality TestingSOFTWARE PUBLISHINGNovember 2019 - January 2020 (2 months)Beijing, ChinaQuality control of AI models for classifying newspaper articles by category.
- VisioTerra,Internship — Data Science on Satellite ImagesCONSULTING AND AUDITSMay 2024 - June 2024 (1 month)77420 Champs-sur-Marne, France• Sentinel-2/LandSat data processing; state-of-the-art agricultural plot detection (Deep Learning).
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Education
- Master Distributed Artificial IntelligenceUniversité Paris Cité2025Développement de modèles ML. Développement d'applications IA. Déploiement. Théorie de l'IA neuro-symbolique.