building ML systems around messy real-world data and occasionally convincing them to work
π open to internships Β· freelance work Β· collaborations
Languages
Python C C++ TypeScript SQL HTML CSS
ML / Data Science
PyTorch Scikit-Learn XGBoost SHAP Pandas NumPy
Backend & Databases
FastAPI Node.js PostgreSQL MongoDB Mongoose
Data Apps & Visualization
Streamlit Power BI Tableau
Cloud & DevOps
AWS Docker MLOps System Design
Tools & APIs
Git Postman Render Claude API
- DSA and algorithmic thinking
- research papers and rebuilding ideas from scratch
- the overlap between ML engineering and software engineering
- whatever catches my curiosity next
you're hiring for ML/data roles, building something in AI, or want to talk about projects, papers, and the weird bugs and failure modes that don't make it into project showcases.


