🌍 Senior Full-Stack Software engineer | ML & AI enthusiast

Welcome to my GitHub! I build tools, experiments, and frameworks in machine learning, generative AI, and modern backend systems. I enjoy learning in public and sharing open-source projects that help others build and explore.

• I’m currently working on Generative AI & ML projects, including a full-stack GenAI Playground with PyTorch, FastAPI, and Docker.
• I focus on designing scalable, low-cost LLM system architectures, emphasizing efficient inference, modular pipelines, and production-ready deployment.
• I enjoy building end-to-end machine learning workflows — from data preprocessing to model training, API design, evaluation, and deployment.
• Ask me about Python, ML/AI systems, LLM infrastructure, backend APIs, and project architecture.

Here are some of my key open-source repositories:

• gen-ai – A full-stack Generative AI Playground with modern deep-learning models, a FastAPI backend, Dockerized setup, and Jupyter support. (Explore and experiment with LLMs and vision models)
• Deep-Learning-LLM-Wounded-Treatment – A practical deep learning project combining CNNs and LLM workflows for domain-specific medical applications.
• AML Detection Platform (NDA) – Built a Dockerized, end-to-end AML system using unsupervised anomaly detection, PCA, and ensemble risk scoring with analyst-facing dashboards.
• Exo Proxy Fortress – Designed and built a secure, high-performance LLM load balancer and proxy layer for distributed AI inference across Exo clusters and Ollama servers.
  Implements intelligent request routing, model-aware load balancing, API key–based security, rate limiting, and application-level cluster management without Kubernetes.
  Extended the system with RAG (Retrieval-Augmented Generation), vector search, and Redis-backed KV caching to significantly reduce latency and inference cost.
  Fully Dockerized with FastAPI, Gunicorn, Redis, MongoDB, ChromaDB, and Nginx for production-ready deployment.

Languages: Python, JavaScript/TypeScript, PHP, SQL
Frameworks: PyTorch, FastAPI, Flask, React, Symfony
Tools & Platforms: Docker, Jupyter, GitHub Actions, REST APIs
AI & ML: Transformers, CNNs, GANs, Diffusion Models, XGBoost, HBOS, Isolation Forest, ECOD

• Large-scale LLM training & fine-tuning
• Cost-efficient LLM inference and system optimization
• Production-grade ML and AI deployment best practices