I design, deploy, and maintain production-grade ML systems — from deep learning models to scalable backend APIs.
My focus is building practical, efficient solutions that connect machine learning research with real-world deployment.
- Python (main)
- SQL, JavaScript, HTML/CSS (hobby)
- C (basic)
- Backend: FastAPI/Django
- Machine Learning: PyTorch, Scikit-Learn, Transformers, XGBoost, LightGBM
- Data & Visualization: Pandas, NumPy, Matplotlib
- Concurrency: Threading, Multiprocessing, asyncio
- PostgreSQL (pgvector), ChromaDB, MongoDB
- Docker, Kubernetes, Nginx
- Google Cloud, AWS, Runpod
- Git, CI/CD pipelines