AI/ML Engineer
Computer Vision · LLM Systems
Computer vision · LLM systems
I build computer-vision and LLM systems that hold up in the real world.
Final-year AI engineer. I take machine-learning models out of notebooks and into systems that run on real hardware — real-time perception, LLM pipelines, and the deployment around them.
Selected systems
2026 · Solo · computer-vision system
Industrial fall detection that runs live on a single mid-range GPU — pose, tracking, segmentation and a temporal model behind one observable service, with no fabricated numbers.
2026
An agentic GraphRAG system where a user's clearance is enforced inside the retrieval path — the model never sees a chunk the caller isn't allowed to read, so it cannot leak it.
2026
My bachelor's thesis: a reproducible benchmark for how reinforcement-learning agents cope when they can only see part of the world — and which architectures recover the missing state.
More on GitHub ↗
What I build with
Where I've worked
Nov 2024 — present
Mar 2026 — Jun 2026
Background
2022 — 2026
University of Vigo
Coursework across machine learning, deep learning, computer vision, reinforcement learning, databases and software engineering.
Highlights
A bit more
I'm a final-year AI engineering student at the University of Vigo, more interested in the gap between a model that works in a notebook and a system that works on real hardware than in either one alone.
Most of my hands-on work has been in computer vision — real-time perception for an autonomous racing platform with Auria — and in LLM pipelines, including a RAG system for clinical data normalization at MicroPort. The thread through both is the unglamorous part: reproducible training, clean deployment, and evaluation that's honest about where things break.
I work in Spanish and English.
Get in touch
Open to AI/ML roles and collaborations.
The fastest way to reach me is email — I read everything and reply to what I can.