AI Engineer & Data Scientist | 5+ Years Software Engineering & Machine Learning 📍 Lleida, Spain (Remote Preferred)
📧 pauagustifernandez3@gmail.com | LinkedIn
I am an AI Engineer who bridges the gap between data science research and production-ready software. With over 5 years of experience in software engineering and leading technical teams, I focus on building maintainable, end-to-end ML systems that deliver measurable business value.
"I focus on building robust ML systems, from data pipelines to deployed models, not just notebooks."
- Agri-Food ML/AI @ IRTA: Developing predictive models for fruit conservation, deploying systems with FastAPI and MLflow for high-frequency inference.
- Generative AI @ Phaser (Co-Founder): Engineered a RAG pipeline with LangChain to query 500+ complex documents and built AI microservices to integrate within Web-based applications.
- Real-Time IoT Monitoring (M.Sc. Thesis): Architected a streaming anomaly detection pipeline using Apache Kafka and Flink, leveraging MLflow for experiment tracking and model versioning to ensure seamless deployment of PV system diagnostic models.
- Software Engineering Leadership: Previously led a team at ICG Group/Hiopos Cloud, managing a multi-tenant e-commerce platform.
- 🥇 1st Prize Award: Best Thesis in the Energy Field by Energy HubLab for designing a Deep Learning Autoencoder to detect hardware failures in solar inverters.
- 🔬 Published Researcher: Co-author of "Visible-near infrared spectroscopy and near-infrared hyperspectral imaging for the detection of T-2 and HT-2 toxins in individual oat grains" in Food Control (2025).
| Category | Tools & Technologies |
|---|---|
| Programming Languages | Python, Typescript, Java, R |
| AI & Data Science | Keras, PyTorch, Scikit-learn, Pandas, NumPy, LangChain, Optuna |
| Engineering & MLOps | AWS, Azure, Kafka, Flink, MLflow, Docker, PostgreSQL, MariaDB, CI/CD |
| Web & Backend | FastAPI, Spring Boot, Django, Angular, Supabase |
| Visualization | Streamlit, PowerBI, Plotly, Matplotlib, Seaborn |
- AI Engineering / Designing Machine Learning Systems (Chip Huyen): My core references for bridging the gap between research and production. Both books emphasize not just building models or AI-driven features, but making them useful in the real world.
- Statistics Without Tears (Derek Rowntree) / The Art of Statistics (David Spiegelhalter): Essential for making abstract statistical ideas feel approachable and meaningful.
- The Pragmatic Programmer (Andrew Hunt & David Thomas): Timeless principles on how to think and act as a professional developer. Many of its lessons can also be applied beyond software.
- Code Complete (Steve McConnell): Deep dive into software craftsmanship. Helps you understand why good practices matter.
- 🏃 Dedicated runner, occasional trail runner, and gym enthusiast.
- 🎣 Passionate about fishing, nature and outdoors.
- 🚀 Interested in how AI innovation transforms the global market.
Let's build something impactful! Connect with me on LinkedIn.