- 💼 Current Role: Senior Full Stack AI Engineer - designing and deploying ML systems at scale
- 🔬 Focus Areas: Applied AI, MLOps, Large Language Models (LLMs), and intelligent automation
- 🧩 Core Strengths: End-to-end ML lifecycle (data → model → deployment → monitoring)
- 🌍 Goal: To advance AI systems that are ethical, explainable, and production-grade
- 🤝 Open to Collaboration: Open-source, AI research, and real-world ML applications
- 🐳 Advanced DevOps Practices: CI/CD, containerization, orchestration.
- 🤖 Machine Learning & AI: Leveraging AI for real-world applications.
- 🔗 Blockchain Technology: Exploring decentralized solutions and use cases.
- Deep Learning (PyTorch, TensorFlow, Keras)
- Natural Language Processing (LLMs, Transformers, RAG, LangChain)
- Computer Vision (CNNs, OpenCV, YOLO, segmentation)
- Model Deployment (TensorRT, ONNX, TorchServe, FastAPI)
- Reinforcement Learning & Generative AI (Diffusion, LLM fine-tuning)
- CI/CD pipelines (GitHub Actions, Jenkins)
- Containerization & orchestration (Docker, Kubernetes)
- Model monitoring, A/B testing, and continuous retraining
- Cloud platforms: AWS, GCP, Azure
- Data pipelines: Airflow, Kafka, Prefect, MLflow
- Full-stack: React/Next.js, Node.js/Express, Python, C++, Go, TS/JS
- Mobile APP: Flutter, React Native, Expo, Swift
- Databases: PostgreSQL, MongoDB, Redis