Building scalable machine learning systems across LLM applications, NLP, computer vision, and predictive analytics with 4+ years of enterprise experience.
Get to know me better
AI/ML Engineer with 4+ years of experience building and deploying scalable machine learning solutions across NLP, computer vision, and predictive analytics. Strong in Python and SQL, with hands-on expertise in frameworks such as Scikit-learn, TensorFlow, and PyTorch for developing and optimizing models. Expert in creating Generative AI and LLM-based applications using LangChain, LangGraph, Hugging Face, RAG architectures, and vector databases to drive intelligent automation. Skilled in designing data pipelines using Pandas, PySpark, Kafka, and Airflow for large-scale data processing. Proficient in MLOps practices including MLflow, Docker, Kubernetes, and CI/CD for reliable model deployment. Experienced with AWS, Azure, and GCP, and capable of delivering actionable insights through Tableau and Power BI dashboards in Agile environments.
Core Focus
Skills and platforms highlighted in the current resume
My journey in the tech industry
Honeywell
Hexaware Technologies
Selected portfolio projects from the earlier site version
Developed end-to-end automated grading model comparing traditional ML algorithms vs. deep learning approaches
Built deep learning pipeline using VGG16, ResNet-50, and Vision Transformers for automated particle identification
Implemented character-level GPT model from scratch to study training dynamics
Developed full-stack music streaming web app with integrated CNN-based music genre classifier
Applied association rule mining and clustering on the UCI Heart Disease dataset
Analyzed 8K+ Netflix titles and explored content diversity impact on stock performance
Academic background reflected in the resume
University of North Texas
Institute of Science and Technology, Tribhuvan University
Let us discuss AI/ML roles, Generative AI initiatives, and applied machine learning work
I am always excited to discuss AI/ML engineering roles, Generative AI initiatives, and production machine learning systems. Feel free to reach out through any of the channels below.