Resume

Technical Skills

  • Programming Languages
    Python, Go, C++, JavaScript, SQL, HTML, CSS, Haskell, Elm
  • Frameworks & Libraries
    TensorFlow, PyTorch, Flask, FastAPI, Streamlit, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Plotly, Celery, Docker
  • Databases
    PostgreSQL, MySQL, SQLite, DynamoDB
  • Cloud Providers
    Amazon Web Services (AWS), Google Cloud, DigitalOcean
  • Tools
    Git, Docker, Jupyter, Postman, Unreal Engine

Work Experience

  • Dec 2024 - Present | Idoven
    Dec 2024 - Present | Product Software Engineer Backend (Full-time)

  • Oct 2018 - Dec 2024 | Cambrian Intelligence SL
    Jul 2019 - Dec 2024 | Software Engineer & Machine Learning Engineer (Full-time)

    • Design and implementation of a machine translation system deployed in AWS leveraging services like API Gateway, Cognito, Lambda, DynamoDB, S3, and CloudFront.
    • API Rest development to expose complex deep learning-based systems and web services using Go and Python (Flask).
    • Full-stack design and implementation of a tool to retrieve atmospheric data from several public sources and expand datasets with this information. Developed a REST API (FastAPI) to expose the service for seamless access and integration.
    • Development of full Machine Learning pipelines for a variety of data sources, from data exploration to model productionization.
    • Full-stack design and implementation of a Machine Learning-based early warning system to anticipate exacerbation in patients with COPD. Use technologies such as TensorFlow, Flask, Celery, and Docker. The system is actively used by a medical team to enhance treatment of about 120 patients with COPD.
    • C++ DLL to deploy deep learning models in environments without internet access and under Windows systems. This DLL is currently used in production by tuna fishing ships for a variety of tasks.
    • Pipeline for 3D data generation using Unreal Engine. This generated 3D data is used to train deep learning models for solving object detection and counting tasks. This model has been deployed and is currently being used.
    • RAG framework utilizing Chroma DB for efficient document embedding. It enables query-based retrieval, semantic search, and contextual document validation.

    Oct 2018 - Jul 2019 | Junior Machine Learning Developer (Full-time)

    • Data preparation, data visualization and ML modeling using healthcare data.
    • API development using Flask.

  • Jun 2018 - Oct 2018 | Sopra Steria
    QA Tester (intern)

Education

  • 2020 - 2021 | Master’s Degree in Logic, Computation and Artificial Intelligence
    Universidad de Sevilla

  • 2014 - 2018 | Bachelor’s Degree in Computer Science - Information Technologies
    Universidad de Sevilla

Licenses & Certifications

  • 2023 | AWS Certified Developer – Associate (link)(link)
    Amazon Web Services Training and Certification
  • 2019 | B2 First Certificate in English (link)
    Cambridge Assessment English

Scientific Publications

  • 2021 | Evolutionary game theory in a cell: A membrane computing approach (link)
    Pedro García-Victoria, Matteo Cavaliere, Miguel A. Gutiérrez-Naranjo, Miguel Cárdenas-Montes
  • 2021 | PBIL for optimizing Inception Module in Convolutional Neural Networks (link)
    Pedro García-Victoria, Miguel A. Gutiérrez-Naranjo, Miguel Cárdenas-Montes, Roberto A. Vasco-Carofilis
  • 2020 | Late Breaking Abstract - Recurrent Neural Networks and environmental data for COPD exacerbation prediction (link)
    Cristobal Esteban, Francisco Javier Moraza, Pedro García, Amaia Aramburu, Fernando Sancho, Leyre Chasco, José Antonio Gutiérrez, Francisco José Conde, Sergio Resino, Cristóbal Esteban

Courses

  • 2020 | Neural Networks and Deep Learning (link)
    Coursera