AI/ML Engineer_

I worked in Banco Santander’s Data & AI department through Hopla! Software, on production machine learning systems and MLaaS services.

• I designed, developed, and maintained internal machine learning, deep learning, and forecasting libraries, alongside end-to-end data and modelling pipelines.
• I developed scalable ML solutions using Azure Databricks and MLflow.
• I researched and implemented methods to improve model performance, interpretability, robustness, and fairness.
• I worked on containerisation, deployment, and monitoring of production models following MLOps practices.
• I worked with infrastructure and server-side environments for model development and deployment.
• I contributed to cross-team initiatives to strengthen platform capabilities and the bank’s AI ecosystem.
• I contributed to migrating ML pipelines from R to Python for integration with Azure and Spark-based environments. The project was completed in around five months and improved workflow scalability and maintainability.
• I performed version migrations of R-based ML pipelines, including refactoring and bug fixing for compatibility with updated environments. This phase was completed in approximately one month with minimal operational disruption.

I co-founded Nebux Cloud SL, my first company, focused on cloud and AI solutions during my tenure.

• I combined leadership responsibilities with digital strategy, brand growth, and AI/ML engineering.
• I contributed to business development, technical project delivery, and company positioning.
• In 2025, I sold my stake and concluded my time at Nebux.

I led the company, combining product and business strategy with team organisation and operations.

• I defined and led the strategic vision across product, operations, marketing, and growth.
• I built and managed multidisciplinary teams and defined how their work was organised and executed.
• I developed and executed the brand identity, corporate communications, and go-to-market strategy.
• I worked on brand visibility and engagement through competitive analysis and performance-based iteration.
• I led business development, partnerships, investor relations, and external company representation.

I developed machine learning and deep learning solutions designed for production use.

• I developed recommendation, semantic search, and sentiment analysis systems using deep learning and embedding techniques.
• I designed and implemented end-to-end solutions, from data processing to model deployment.
• I applied supervised and unsupervised learning methods to production-oriented use cases.
• I collaborated with cross-functional teams to translate business requirements into ML systems.
• I worked with clients and academic partners to define validation strategies and interpret experimental results.

I managed digital communications and social media strategy to promote the organisation’s projects and activities.

• I developed and executed a content strategy to increase online visibility.
• I created and managed digital content across social media platforms.
• The strategy added more than 800 followers to the organisation’s social media presence.
• I improved engagement and content reach through targeted posts and consistent publishing.

I designed, implemented, and operated DevOps and SRE solutions for more than ten client environments.

• I designed and operated platforms using Docker, Kubernetes, and Helm to support scalable, reliable services.
• I developed CI/CD pipelines with GitHub Actions and Bitbucket Pipelines to automate builds, testing, and deployments.
• I managed infrastructure and configuration with Ansible in Linux environments, across virtual machines, AWS, and GCP.
• I led platform migrations, service transitions, and production upgrades to maintain service continuity and minimise downtime.
• I implemented monitoring and observability with Prometheus and Grafana and centralised logs with Loki and Elasticsearch.
• I contributed to log analysis and predictive alerting strategies using Alertmanager and custom rules.
• I participated in on-call rotations, incident response, and root cause analysis to maintain service availability.

I researched machine learning applications for analytical chemistry, combining experimental work, model development, teaching, and student project support.

• I applied machine learning to pattern recognition, feature selection, and predictive modelling using complex analytical data.
• I developed and validated supervised and unsupervised models for classification and regression, including PCA, clustering, SVM, Random Forest, PLSR, and Elastic Net.
• I developed analytical methodologies using instrumental techniques such as GC-MS and Vis-NIR and electronic nose systems.
• I integrated spectroscopic data and electronic nose signals with ML models for pattern recognition and prediction.
• I performed feature engineering and selection with Boruta, genetic algorithms, and RFE.
• I designed, deployed, and monitored R Shiny applications on ShinyApps.io so models could be used and results delivered to end users.
• I developed reproducible data analysis and modelling workflows in R.
• I taught undergraduate General Chemistry and Analytical Chemistry courses.
• I supervised student projects and supported academic research activities.

I studied the presence and accumulation of trace elements in edible mushrooms from southern Spain and northern Morocco.

• I determined toxic and non-toxic trace elements using inductively coupled plasma mass spectrometry (ICP-MS).
• I used data visualisation, descriptive statistics, clustering, and PCA to identify patterns in the samples.
• I linked element accumulation to external factors or intrinsic sample characteristics.
• I interpreted the results from a food safety perspective, providing information relevant to businesses and consumers.

I worked on sample preparation and elemental analysis using inductively coupled plasma techniques.

• I optimised block acid digestion to make sample preparation faster and more reproducible.
• I quantified macroelements and micro- and ultratrace elements by combining ICP-AES and ICP-MS for accurate results.
• I applied statistical methods to validate results and improve their interpretation.

I investigated doping in organic–inorganic hybrid perovskites to improve stability and tune optical properties for photovoltaic applications.

• I studied the effect of A-site doping in the perovskite structure using combinations of two or three cations.
• I characterised the samples using UV-Vis spectroscopy and X-ray diffraction.
• Doping produced perovskite nanopowders with improved structure and optical properties.
• The materials FA0.1MA0.9PbI3 and FA0.1Cs0.1MA0.8PbI3 had a stable cubic crystalline structure and band gaps of 1.48 eV and 1.47 eV, respectively.

I supported research in the SCEM group of the University of Cádiz’s Physical Chemistry department.

• I analysed synthetic diamonds using Raman spectroscopy.
• The work focused on industrial applications, particularly power devices.

I worked on formulations and process control to improve hologram stability and uniformity.

• I improved the developing formulation to produce more stable, uniform holograms.
• I monitored pH, density, temperature, and humidity to maintain appropriate process conditions.
• I managed quality control and process records, reducing incidents.