Welcome to my GitHub profile!
I'm an AI/Machine Learning Engineer with experience building scalable, production-grade intelligent systems for the energy, oil & gas, and industrial sectors. My work focuses on developing end-to-end AI/ML solutions that support real-time decision-making, improve operational efficiency, and create measurable business impact.
I have hands-on experience in machine learning pipelines, distributed inference, real-time anomaly detection, feature engineering, model development, LLM integration, and MLOps. I enjoy building reliable AI systems that move beyond experimentation and deliver value in production environments.
- 💼 Experience: AI/ML engineering for energy, oil & gas, industrial systems, healthcare analytics, NLP, and LLM applications.
- 🧠 Core Focus: End-to-end ML pipelines, real-time anomaly detection, distributed inference, LLM integration, and production AI systems.
- ⚙️ MLOps: Skilled in deploying, monitoring, and maintaining scalable machine learning solutions.
- 🌱 Passion: Turning complex data into intelligent systems that help organizations make better decisions.
- ⚡ Fun Facts: I enjoy music, traveling, and playing cricket in my free time.
- Languages: Python, R, SQL
- Cloud & Platforms: AWS, Microsoft Azure, Databricks
- Big Data: Spark, PySpark, Hadoop
- Machine Learning: Scikit-learn, XGBoost, TensorFlow, PyTorch
- NLP & LLMs: Hugging Face, Transformers, BERT, OpenAI, LangChain, RAG
- Databases: PostgreSQL, MongoDB, DocumentDB
- MLOps: Docker, GitHub Actions, MLflow
- Web Frameworks: Flask, FastAPI
- Building scalable AI/ML systems for real-world industrial problems.
- Exploring LLMs, RAG, AI agents, and production-ready GenAI applications.
- Improving data workflows, model deployment, and MLOps pipelines.
- Creating practical AI projects that connect machine learning research with business impact.
“Turning data into insights, one model at a time.”