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Curriculum Vitæ

{% include contact.html %}

Professional Profile

Consolidated career path in orchestrating Generative AI agents, optimizing models through advanced prompt engineering, evaluating LLMs, and developing RAG architectures. Backed by previous experience in the publishing sector, bringing demanding analytical criteria to content structure and language quality. Currently focused on designing advanced conversational systems, mitigating biases in language models, and validating complex data flows within production environments.


Professional Experience

Repsol LCG

Data Analyst Intern Nov 2025 – May 2026

  • Data integrity: Developed Python scripts for cleaning and validating operational data from renewable energy assets. Implemented automated time-series checks prior to ingestion into MongoDB to ensure high-fidelity data flows.
  • Generative AI: Collaborated directly with the technical lead in defining requirements and conceptual design for GenAI use cases (PoCs), including functional documentation for the proposed solutions.
  • Data Standardization: Normalized and unified data from multiple heterogeneous sources (SQL Server, Oracle, PostgreSQL) to facilitate subsequent analysis and ensure data traceability.

Whitehole Data

Computational Linguist Intern May 2025 – Aug 2025

  • LLM Optimization: Designed a recursive prompt engineering workflow backed by a judge agent to align the performance of lightweight models with more robust ones, reducing computational costs without sacrificing output quality.
  • Evaluation and Quality: Detected and corrected overfitting issues by identifying outliers in training data and refining model behaviour through controlled prompt iterations.
  • Applied NLP: Implemented a hybrid NER system (spaCy + LLMs) to extract structured entities from financial news and built Plotly dashboards for pipeline visualization.

Editorial Sector

Digital Publishing & Content Production 2020 – 2024

  • Digital Content Management: Led the development of multimedia educational materials, ensuring complex data structures (HTML/XML) met product quality standards.
  • Metadata Optimization: Managed quality control (QA), indexing, categorization, and metadata management within structured CMS platforms (Alfresco, Blinklearning) to ensure resource traceability.
  • Agile Coordination: Managed external collaborators and design teams under agile methodologies (Scrum) and demanding production schedules.

Education

Specialization in Machine Learning Engineering & AI on GCP

CFTIC Expected July 2026

MSc in Language and Artificial Intelligence

Universidad Autónoma de Madrid 2024 – 2025

MA in American Studies

Universidad Complutense de Madrid 2019 - 2020

BA in English Studies

Universitat de Barcelona 2013 - 2029


Technical Skills

NLP & Generative AI

  • CrewAI
  • LangChain
  • OpenAI
  • RAG systems
  • Adavnced Prompt Engineering
  • spaCy
  • Transformers
  • Rasa
  • Dialogflow
  • Cognigy
  • LLM evaluation

Cloud & MLOps

  • Google Cloud Platform (GCP)
  • Vertex AI
  • BigQuery
  • Cloud Storage
  • Dataprep
  • ML pipelines deployment

Modelling & Machine Learning

  • TensorFlow
  • Scikit-learn
  • Tokenization
  • Lemmatization
  • Part-of-speech (POS) tagging
  • Word embeddings
  • Sintactic/semantic analysis
  • NER (Named Entity Recognition)

Data Engineering

  • Python
  • Pandas
  • Regex
  • MongoDB
  • SQL (PostGreSQL, Oracle, SQL Server)
  • Sata validation
  • Web Scraping (Beutiful Soup)
  • REST APIs

Conversational Design & UX

  • Dialogue flow architecture
  • Message lifecycle modelling
  • Intent definition and training
  • UX writing
  • Sensitive data management

Tools & Methodologies

  • Git (GitHub/GitLab)
  • JSON
  • XML/XSL
  • Jupyter Notebooks
  • Plotly
  • Agile Methodologies (Scrum)

Certifications

  • Cognigy Academy Mastery Track 1, 2 & 3
  • IBM User Experience Design
  • IBM Data Fundamentals
  • Founderz Responsible AI & Prompt Engineering

Languages

  • Spanish (Native)
  • English (C1)
  • Catalan (Professional)
  • German (A2)
  • French (A2)