Etienne Ferrandi
Hello! I'm Etienne Ferrandi, a Lyon-based AI Engineer focused on turning research into practical, deployed LLM-powered solutions.
About
Hello! I’m Etienne Ferrandi, a Lyon-based AI Engineer focused on turning research into practical, deployed LLM-powered solutions. I enjoy extracting structured knowledge from large document collections, building RAG pipelines, and deploying LLMs in production on AWS Bedrock and local GPUs.
I collaborate with researchers and civil servants to create augmented, reliable answers and semantic graphs that help people navigate complex information. In my work, I blend data engineering, NLP, and software development to deliver usable tools for real-world challenges.
Industry experience
- Education
- Professional Services
- Government
- Software & Internet
- Non-Profit Organization
Work experience· 5 roles
Building a conversational agent with langgraph / langchain on a medical kit tracking software; RAG with qdrant; Cloud provider for LLMs: Bedrock; Deployment on AWS: Bedrock Agentcore
Extraction of structured knowledge from a large quantity of documents; XML/TEI data extraction; Data mining to identify unstructured bibliographic data with quantized LLMs: inference (vllm) on local GPUs from ENS Lyon (no cloud provider used); Structuration of those messy data via RAG (qdrant KB) and constraint generation (Pydantic); Fine-tuning of different llms: encoder-decoder mt5, decoder-only llama 3.1 8B (transformers)
Building a RAG agent: Albert API (chunking, embedding in a vector DB of XML data, use of different llms to provide augmented answers to public servants); Extraction of bibliographic unstructured data on 20th century archives of the Historical Service of the Ministry of Defence with SOTA OCR/HTR models; generation of XML/EAD encodings of archive collection inventories; Project management support for the implementation of a semantic graph tool for research data for the IRD
Education
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