My professional career spans more than 15 years combining scientific research, software development, and technical leadership. From my beginnings in programming at age 7 to my current role as an AI consultant, I have maintained a focus on technical excellence and innovation.
AI/ML Engineer and Systems Architect with a unique technical duality: the ability to design intelligent agents at a high level (Python, LLMs, RAG) and more than 15 years of experience to optimize their performance at a low level (C++, HPC). My goal is to bridge the gap between research and production, building robust, efficient, and scalable AI solutions from "bare metal" to the final application.
My trajectory in the Python/Anaconda ecosystem, applied for years in academic (UB, UNED) and professional environments, has consolidated me as an expert in the complete data lifecycle. This approach is grounded in an early passion for science, where my first astronomical data analyses were performed manually with analog telescopes, forging a fundamental understanding of information that I now apply to the design of complex systems.
Academic Background
Currently pursuing Physics Degree | UNED
Continuing my education in physics to deepen the theoretical foundations I apply in my AI and quantum computing projects.
Physics and Data Analysis Degree | Universitat de Barcelona (2014 - 2017)
Solid training in computational physics, data analysis, and scientific programming that laid the foundations of my current expertise.
Object-Oriented Programming Course | Aula de Informática (Barcelona) (September 1999 - June 2000)
First formal steps in programming that complemented my self-taught learning since age 7.
Fundamentals and Self-Taught Learning
My training in computing and astronomy began at age 7 with systems like Spectrum 48K and Commodore Amiga 500, developing a practical and self-taught approach that has defined my career.
- Admitted early to programming academies (GWBASIC at age 12)
- Member of the Astronomical Society (SAEA) at 14, applying Amiga Basic for complex astronomical data analysis
- Self-taught mastery of C and assembly with foundational texts like "The C Programming Language"
- Self-taught research on "Theory of Everything" (TOE) and experience in strategic security sector
Professional Experience
Freelance Machine Learning Consultant and AI Researcher | Quantica Solution (2018 - Present)
I started this project as a personal exploration in quantum algorithm design, currently offering consulting services based on:
- Expert consulting in Machine Learning and Data Science (Python, Scikit-learn, Pandas)
- Data pipeline development (ETL, web scraping, network analysis)
- Research and development in advanced AI, including practical work with LLMs and RAG architectures
- Experience in R&D computer vision projects, integrating OpenCV in both C++ and Python
Senior AI / Deep Learning Engineer | IA Business Consulting (2017 - 2024)
- End-to-end design and implementation of predictive systems based on Deep Learning (GNNs, Embeddings)
- Creation and management of ML workflows in the cloud (AWS, GCP, Azure) for training and inference
- Expert use of Python and frameworks like TensorFlow/PyTorch to bring research models to production
Lead Developer / Systems Architect | DragonArk (2017 - 2023)
- Led technical development for the hybridization of analog and digital systems, with a focus on assisted home automation for dependent people
- Developed a system based on a conglomerate of sensors and predictive models, using Python for agile development and modern C++ for optimization of critical bottlenecks (achieving a minimum 10% performance increase)
- Encapsulated sensor drivers (cameras, microphones) written in pure C in Python interfaces to democratize their access and control
- Implemented computer vision algorithms with OpenCV and designed an architecture oriented to asynchronous orchestration of specialized LLMs using FastAPI and the MCP protocol
Director of Innovation and Digitalization | GlobalBTS (2020 - 2024)
- Led digital transformation projects, leading the ETL process with Pandas and SQL to feed Deep Learning models from legacy databases
- Applied my knowledge of physics and endomorphism diagonalization to linear regression algorithms to optimize predictive models
- Implemented conversational agents with NLP and RAG architectures that allowed users to query clean data
Development Engineer (Physics Engines and C++ Optimization) | Macktek (2010 - 2017)
- Led the development of a modern C++ physics engine, achieving a 30% reduction in calculation time and enabling real-time simulation of more than 1000 objects
- Implemented the engine with minimal STL dependency, creating from scratch an optimized linear algebra library. Integrated Coriolis acceleration in exterior ballistics calculations for greater precision
- Programmed enemy AI, allowing a machine-controlled sniper to compensate for Coriolis force in their shot correction, demonstrating a high level of physical detail