Data & ML Engineer with 6+ years of experience across machine learning, data science, and production ML systems.
I currently work at PicPay, building systems for monitoring credit models in production. More recently, I've been exploring how LLMs and agentic workflows can improve our processes.
My background spans the ML lifecycle, from developing credit scoring models to building the infrastructure and tooling needed to monitor and understand models in production.
- 🤖 AI & agentic workflows: building structured, tool-using workflows for data analysis, automated reporting, and knowledge-intensive tasks.
- 📊 Production ML: monitoring model performance, stability, calibration, drift, data quality, and hundreds of production features.
- 🛠️ Personal projects: building tools around problems I find interesting and publishing some of them here.
A structured workflow for continuous career development, bringing together 1:1 notes, development plans, and performance reviews.
Built around Markdown, JSON Schema, automated validation, GitHub Actions, and an AI skill-based workflow, with an emphasis on keeping data portable, structured, and human-readable.
Machine learning projects developed during my M.Sc. at UFPE. The main project involved translating a scientific paper on kernel fuzzy clustering into working code, implementing its mathematical formulation with vectorized matrix operations for efficient computation.
Programming & Data: Python · SQL · PySpark · Pandas
Machine Learning: scikit-learn · PyTorch · XGBoost · LightGBM · MLflow · Optuna
Data & ML Platforms: Databricks · AWS
AI Engineering: LLMs · Agentic Workflows · Tool Use · Structured Outputs
I hold an M.Sc. in Computer Science and a B.Sc. in Electronics Engineering, both from UFPE.
Outside of work, I'm usually reading, running, hiking, or learning something new.