AI/ML Engineer building production-oriented ML systems for agribusiness, one of the most data-rich and underserved verticals for applied AI globally. Work spans RAG systems with hallucination detection, on-device computer vision, time-series forecasting, and end-to-end NLP pipelines.
Open to remote ML/AI engineering roles — international or Brazil-based.
| Project | What it solves | Stack |
|---|---|---|
| sb100_agents | Producers lack scalable access to precise agronomic knowledge; agronomists are costly and research literature is inaccessible at field level | Python · FastAPI · Qdrant · Ollama |
| visiosoil-app | Soil texture assessment requires lab analysis or trained specialists; neither viable for large properties in low-connectivity rural environments | Flutter · Dart · TFLite · Riverpod |
| pma-weather-forecasting | Short-term temperature forecasting for agriculture, energy and public-safety planning across 211 countries | Python · LightGBM · scikit-learn · Prophet |
| tweet-sentiment-analysis | Generic sentiment classifiers fail on social-media language; slang, sarcasm and platform-specific syntax cause unreliable outputs | Python · Rust · HuggingFace · Polars |
Languages & Data
ML & Deep Learning
LLM & RAG
Backend & Mobile
Cloud & Tools
