Building deployable ML systems that ship, not just demo notebooks
Focused in Applied ML, Data Science and Python Backends. Messy Data In --> Reliable Predictions Out --> Deployed APIs.
I care deeply about the fundamentals: clean feature engineering, rigorous evaluation, and shipping code that works.
| Category | Technology Stack |
|---|---|
| π¨βπ» Languages | |
| π§ Machine Learning | |
| π Search Arch & LLMs | |
| π Backend & APIs | |
| π¨ Frontend & UI | |
| ποΈ Databases | |
| π οΈ Tools & DevOps |