Scaling LLMs & Autonomous Agentic Workflows at Production Grade
🎯 11+ years leading AI teams across 3 continents
🤖 25+ engineers directed across cross-functional teams
💰 $12MM+ revenue impact via AutoML platform
🏭 60,000+ models deployed to production globally
🔄 82% manual labeling replaced by agentic workflows
🎓 École Centrale Paris · MIT Sloan (Visiting)
🌍 US Green Card Holder & EU Citizen
I build and scale production-grade AI systems — from fine-tuning foundation models (RLHF/DPO/SFT) to orchestrating multi-agent workflows with LangGraph and MCP. My focus is bridging the gap between research and high-impact business automation.
Current obsessions: Agentic AI · LLM-as-a-Judge · Responsible AI · Synthetic Data Generation
| GenAI & LLMs | Infrastructure | Languages & Data |
|---|---|---|
| LLM Fine-tuning (RLHF/DPO/SFT) | Vertex AI · SageMaker | Python (Expert) |
| RAG · LangGraph · MCP | Kubernetes · Docker | SQL · BigQuery · Snowflake |
| LoRA/QLoRA · Quantization | MLflow · CI/CD | PyTorch · JAX · TensorFlow |
| Prompt Engineering | Pinecone · FAISS · Elasticsearch | Apache Spark · Pandas |
| Gemini · Llama · Claude · GPT-4 | vLLM · DeepSpeed · FSDP | Hugging Face Transformers |
🤖 Agentic Orchestration Designed multi-agent workflows automating 82% of manual labeling, improving processing speed by 35% | 🛡️ Responsible AI Architected "LLM-as-a-Judge" framework for hallucination detection — 99.9% safety compliance |
💡 AutoML Platform Built platform generating $12MM in incremental revenue with 60,000+ production models | ⚡ Edge Optimization Led quantization (GGUF/FP8) and distillation for on-premise deployment under strict privacy constraints |
🔍 Multimodal Search Integrated CLIP-based embeddings with Pinecone, reducing search latency by 60% | 🧬 Synthetic Data LoRA-finetuned generation engine boosting model coverage by 45% for low-resource categories |
Open Food Facts — Lead AI Contributor
- Architected a VLM-based OCR system for 3M+ product images (300% ingestion speed improvement)
- Built deep learning classifier for Nutri-Score prediction from ingredient lists
Community
- 🏅 Winner — French Government Food Data Hackathon (2024)
- 🧑⚖️ Judge — Devpost, AiGoLearning, NextAI, Hackathon Raptors (2025)
- 🎓 Trainer — EUROSAE: "The Renewal of Artificial Intelligence" (2024)
| Institution | Focus | |
|---|---|---|
| 🇫🇷 | École Centrale Paris — MSc Engineering | Quantitative Research, ML, Applied Math |
| 🇺🇸 | MIT Sloan — Visiting Student | AI, Statistical Learning, Generalization Theory |
Certifications: AWS ML Specialty (910/1000) · AWS Solutions Architect · CAPM (PMI)
- Generalization Bounds for Learning with Linear and Quadratic Side Knowledge — MIT · arXiv:1405.7764
- Batch Process Monitoring by DTW and K-means Clustering — AIChE Annual Meeting 2015
🌐 French (Native) · English (Fluent) · German (Intermediate)
Let's build something remarkable together.
