AI Engineer at IBM where I architect production-grade Generative AI systems for IBM customers and business partners.
Beyond my work at IBM, I maintain Ad Astra AI—a technical blog documenting production-ready AI engineering projects, sharing deep-dives on building, deploying, and scaling real-world AI systems. My flagship project, SentiWiki AI, is an end-to-end agentic RAG system deployed on AWS ECS for querying ESA Copernicus Sentinel mission documentation
Previously, one year as a Solutions Architect at Huawei gave me deep expertise in cloud architectures, which I've further validated through AWS certifications (ML Specialty, Solutions Architect Associate, AI Practitioner) and Databricks Data Engineer certification.
Currently also an Associate Professor in Machine Learning at UAX University, where I designed and deliver comprehensive curricula for Machine Learning I & Machine Learning II courses to 20+ undergraduate students in the AI & Computation degree program.
IBM
Skills: Python · Elasticsearch · PyTorch · AWS Bedrock · LangGraph · FastAPI · Docker · Git · CI/CD · Agents
UAX University
Associate Professor in Machine Learning in the AI and Computation Degree at University UAX. I created all the theory and coding labs for the Machine Learning I & Machine Learning II curricula for 20+ students.
Huawei
Solutions Architect responsible for Spain's hybrid cloud projects using Huawei Cloud Stack (HCS)
Huawei
Solutions Architect responsible for Spain's hybrid cloud projects using Huawei Cloud Stack (HCS)
Universidad Carlos III de Madrid
Relevant Courses: Machine Learning, Deep Learning, Computer Vision, Data Modelling, NLP, Information Theory.
Universidad Carlos III de Madrid
Relevant Courses: Supervised/Unsupervised Learning, Reinforcement Learning, Transfer Learning, Databases, Neural Networks, Deep Learning, Programming (Python,R,SQL, Scikit-Learn), Statistical Learning, Data structures, Big Data.
AMAZON WEB SERVICES
AMAZON WEB SERVICES
DATABRICKS
AMAZON WEB SERVICES
In a practical workshop at PyConES (biggest python conference in Spain), I instructed over 50 participants on how to build a multimodal RAG (Retrieval-Augmented Generation) pipeline from the ground up. The complete solution adhered to industry best practices, using Python and IBM's robust open-source library, Docling, for intricate document processing.
Access workshopApplied Optics
First-author of a study published in Applied Optics: Developed using python a deep learning segmentation algorithm (feature pyramid network with pre-trained encoder) for anterior eye OCT images, achieving 93.2% accuracy and 0.34 s/image processing.
View publicationLifelong passion for football, tennis, running, and calisthenics, with a commitment to regular practice and personal fitness.
Enjoy reading, particularly autobiographies and reflective literature, to gain new perspectives and insights.
Maintain a personal blog focused on sharing lessons from exceptional individuals through storytelling; publish weekly to an engaged audience of approximately 200 readers.
Enjoy exploring new cultures and destinations, fostering adaptability and a global outlook.
Use the "Download PDF" button or press Cmd/Ctrl + P to save or print this CV