Sergio Medina Muñoz
@sergiomedina
I build reliable local RAG systems with traceable, accurate answers and verifiable citations.
What I'm looking for
I independently built and evaluated GRAIA, a scalable fully local RAG system for academic use cases, as my Computer Engineering thesis at the University of Granada. It earned a 10/10 with the committee's distinction.
I designed its web and PDF ingestion, hybrid dense-embedding and BM25 retrieval, Reciprocal Rank Fusion, cross-encoder reranking, MMR diversification, and local Llama 3.1 8B generation through Ollama. I also built out-of-domain and faithfulness safeguards plus citation verification, then benchmarked the system with 74 questions; it improved factual accuracy from approximately 5% to 87%, delivered 100% verifiable citations, and maintained sub-five-second latency on a consumer GPU.
Experience
Work history, roles, and key accomplishments
AI/ML Engineer
GRAIA
Independently designed, built, and evaluated GRAIA, a scalable, fully local RAG system for the academic domain, achieving 10/10 with distinction. Focused on reliability with out-of-domain gates, faithfulness safeguards, and citation verification.
Education
Degrees, certifications, and relevant coursework
Universidad de Granada
Grado en Ingeniería Informática, Computer Science
2016 - 2026
Pursued a degree in Computer Engineering, focusing on computer science fundamentals and completing a thesis on a local RAG system.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Website
github.com/sergiomediJob categories
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