Designed and fine-tuned LLM-powered prototypes to analyze farmer queries, implementing prompt engineering and LoRA-based tuning for domain-specific NLP tasks. Led computer vision pipelines (CNNs, ViT) for plant disease detection, boosting classification accuracy by 20% using PyTorch. Owned end-to-end data engineering workflows, building scalable pipelines in Python (Pandas, NumPy, Scikit-Learn) and SQL for preprocessing agricultural datasets. Leveraged transformer-based models (BERT, CLIP variants) to integrate text and image for crop health analysis. Created interactive dashboards (Power BI, Tableau) to visualize model outputs and drive stakeholder decision-making.

Software Development Intern at N-Tech Solutions

July 1, 2022 - October 6, 2025

Created a Stock Consumption Management System to streamline inventory tracking and automate canteen transactions, reducing manual record-keeping errors by 60%. Implemented a SQL database schema to manage 1,000+ stock items and 1,500+ daily transactions efficiently. Built a real-time dashboard using JavaScript to visualize stock levels and transaction alerts, enabling intelligent inventory management and faster decision-making.

Machine Learning & Web Developer Intern at Exposys Data Labs

December 1, 2021 - October 6, 2025

Led and constructed a responsive, multi-page tourism platform using HTML, CSS, and JavaScript, increasing site traffic by ~20% through responsive design and enhanced user experience. Modularized frontend architecture with asynchronous AJAX-based REST API integration, reducing page load time by 35% and improving UI scalability. Tuned MySQL queries and indexed critical tables to reduce retrieval time by 50%, while implementing polling-based real-time update support for concurrent user sessions. Built ML models using Python, TensorFlow, and Keras, and deployed for scalable inference, while experimenting with Amazon Bedrock for generative AI–based recommendation enhancements, increasing user engagement by 25%.