Designed and developed advanced AI and Generative AI solutions for academic research, including large-scale data analysis, knowledge discovery, and decision support. Built RAG architectures integrating LLMs with vector databases for context-aware question answering over domain-specific knowledge repositories. Developed conversational AI systems using OpenAI GPT, Llama, and Hugging Face with LangChain and prompt engineering. Implemented NLP pipelines for semantic search, document summarization, topic extraction, information retrieval, and literature review workflows. Built scalable vector search using Pinecone, FAISS, and Chroma DB. Created AI agents/workflow automation orchestrating tools, APIs, and data sources. Implemented MLOps frameworks for experiment tracking, model versioning, automated deployment, monitoring, and lifecycle management using MLflow, Docker, Kubernetes, and Airflow. Leveraged cloud services including Azure OpenAI, AWS SageMaker, and GCP Vertex AI; performed evalua

Software Engineer at MEL Systems and Services Ltd., India

September 1, 2022 - December 31, 2023

Built end-to-end machine learning pipelines for operational efficiency, automation, and insights from structured/unstructured data. Implemented supervised and unsupervised models including Random Forest, XGBoost, Logistic Regression, K-Means, and Gradient Boosting. Developed NLP solutions for document classification, sentiment analysis, and entity extraction. Engineered scalable ETL pipelines using Python, SQL, and Spark. Created predictive maintenance and real-time anomaly detection frameworks. Tuned models via cross-validation and hyperparameter optimization, and presented insights using Power BI and Tableau. Automated deployment with Docker/Kubernetes and CI/CD, and integrated ML services into enterprise apps via REST APIs and microservices. Participated in model governance and collaboration with software/QA/infrastructure teams.

Software Engineer at MEL Systems and Services Ltd.

September 1, 2022 - December 31, 2023

Designed and developed enterprise machine learning solutions to improve operational efficiency, automate business processes, and generate insights from structured and unstructured datasets. Built end-to-end ML pipelines from data collection/preprocessing and feature engineering to training, validation, deployment, and monitoring. Implemented supervised/unsupervised models including Random Forest, XGBoost, Logistic Regression, K-Means, and Gradient Boosting. Developed NLP solutions for document classification, sentiment analysis, entity extraction, and automated information retrieval. Engineered scalable ETL pipelines using Python/SQL/Spark to ensure data quality and consistency. Created predictive maintenance and real-time anomaly detection frameworks. Collaborated with stakeholders to define success metrics and translate requirements into AI solutions. Optimized models using hyperparameter tuning, feature selection, cross-validation, and ensemble learning. Built dashboards/reports in