Across three consecutive internships, I followed the AI product stack from machine learning model development to applied deployment and front-end delivery.
As a Machine Learning Intern at Enginow, I built predictive models with Scikit-learn, feature engineering, and k-fold cross-validation. The models improved held-out accuracy by about six points over the baseline.
At Smart Bridge, I built a TensorFlow and OpenCV pipeline for real-time plant disease classification, reaching about 90% validation accuracy. I also shipped a Streamlit app for image upload and inference, with end-to-end latency under two seconds.
As a Frontend Developer Intern at Mr. Technical Veer Digital Services, I built more than 10 responsive React.js pages using a reusable component library. My projects include an industrial-manual RAG system, a multi-agent blog workflow, and computer vision apps for leaf disease detection and yoga pose identification.
