About

Hi, I'm Álvaro (OTEOPE) 👋 I am an aspiring Machine Learning and MLOps Engineer focused on building modular ML pipelines, auditing data quality, and benchmarking models on real-world datasets.

My goal is to bridge the gap between experimental data science and software engineering by creating clean, scalable, and reproducible AI systems.

🛠️ Core Stack & Tooling ML & Data Science: Python, PyTorch, Scikit-learn, XGBoost, CatBoost, Pandas, NumPy, PyArrow.

MLOps & Engineering: MLflow, Async ETL Pipelines, Parquet Storage, Git/GitHub, Linux.

Environment & Tools: VS Code, Typst, Obsidian.

🚀 Key Projects & Focus Clash of Clans ML Lab: A multi-stage machine learning research suite featuring end-to-end async data extraction, streaming JSON auditing, Parquet ETL pipelines, and multi-problem model benchmarks (classification, regression, ablation studies, and stacking ensembles).

Chess Opening Predictor: A pipeline reconstructing board states at move 10 to evaluate how much predictive signal opening positions hold relative to player ELO.

📬 Connect with Me X (Twitter): @oteopeml

GitHub: github.com/oteope

Feel free to reach out for collaborations, feedback on articles, or discussions on ML architecture!