I build resilient, high-performance AI systems that bridge the gap between datacenter-scale reasoning and edge-constrained reality. Currently a Student-Entrepreneur at Paris-Saclay (Pépite PEIPS) and an invited attendee at OpenAI DevDays.
- Patent Holder (FR2511116): Invented a hybrid RAG architecture for stateful AI communication over low-bandwidth networks (2G/SMS).
- StepFun Contributor: Engineered a local deployment architecture for Step-3.5-flash on Apple Silicon (PR #14 merged in official cookbook).
- Amundi R&D: Architected "Alpha Narratif," a full-stack market simulator modeling narrative warfare in quantitative finance.
- Infrastructure: Bare-metal Homelab (Arch Linux, AMD ROCm), Apple Silicon (MLX), Edge IoT (Raspberry Pi).
- AI/ML: Distributed Inference, Diffusion LLMs (dLLMs), RAG pipelines (ChromaDB, SmolDocling).
- Engineering: Python (Asyncio), C++, React/TypeScript, MLOps (Docker, Netdata).
| Project | Concept | Tech |
|---|---|---|
| Patent-Low-Bandwidth | Stateful AI over 2G/SMS | Python, RAG, ChromaDB |
| Step-3.5-Flash | Local Agentic Sandbox (PR #14) | Apple Silicon, MLX |
| Speech-Pipeline | Real-time S2S with Barge-in | MLX, Python, Latency-Optimized |
| Enigma-Shell | Natural Language VM Control | JavaScript, v86, Local LLMs |
- LinkedIn: in/theophile-lafargue
- Substack: Technical Deep Dives
- Focus: Open to collaborations in Quant Finance Infra and Distributed AI Systems.
