The interview process was smooth and well-structured. It started with an online aptitude and technical assessment, followed by two rounds of interviews. The first round focused on core technical skills, and the second focused on behavioral and situational questions. The panel was friendly and gave time to think before answering.

They asked, “Can you explain a project where you solved a real-world problem using data or AI?”

I described my capstone project on hydroponic disease detection using Fast R-CNN, focusing on how I built the dataset, trained the model, and improved accuracy through image preprocessing.