At Tika Data Services, I work as a Data Annotator, specializing in precise data labeling to enhance machine learning and geospatial analysis capabilities. My role involves handling complex datasets, including orthophoto and LiDAR projects. For orthophotos, I contribute to accurate geographical mapping by annotating high-resolution aerial images, focusing on details such as land use, vegetation, and urban features. In LiDAR projects, I work with laser-generated point clouds, annotating topographical and structural data to assist in the creation of accurate 3D models and elevation maps. This experience has strengthened my skills in interpreting geospatial data, ensuring high-quality annotations, and contributing to data reliability for diverse applications, including environmental monitoring, urban planning, and infrastructure management.

During my internship at Aaram Developers, I worked on two key projects: the School Management Task and the Easy Bank Task. In the School Management Task, I helped design and implement a comprehensive system for managing student and teacher data. This included student admissions, class allocations, mark entry, and generating detailed reports. The system also enabled teachers to manage subjects and report data while allowing administrators to have full control over the system's operations.For the Easy Bank Task, I contributed to developing a streamlined banking application designed to simplify key banking functions such as account management, transaction tracking, and customer service interactions. The focus was on creating a user-friendly interface that ensured security and efficiency, making banking operations seamless for both users and bank staff.Both projects enhanced my skills in backend development, data management, and creating intuitive front-end experiences, utilizing Python, Django, and other web technologies.

At Objectways, I gained extensive experience in data annotation, working on key projects like Keypoints, LiDAR, Dumbledore, and Kiwi. My role involved meticulously labeling and annotating data to ensure high-quality datasets for machine learning models. In the Keypoints project, I focused on annotating precise points of interest in images, crucial for tasks like facial recognition and pose estimation. The LiDAR project involved working with 3D point clouds, where I annotated objects in complex environments to support autonomous vehicle systems. The Dumbledore project sharpened my skills in labeling high-volume datasets with a focus on precision, ensuring seamless integration into AI models. With Kiwi, I contributed to annotating detailed object features for AI-driven applications. Through these projects, I developed a deep understanding of data quality, accuracy, and the importance of detail in the annotation process, helping to improve AI and machine learning outcomes.