Mounika Bandaboina

AI Data Annotation specialist with experience in computer vision labeling, AI evaluation, and data quality analysis. Skilled in analyzing AI-generated images and videos, detecting inconsistencies, and creating accurate training data. Focused on precision, consistency, and strict adherence to annotation guidelines.

Bounding Box Annotation Specialist - AI Training Data Macgence

(2024-01 - 2024-06)

Tools Used: Label Studio, CVAT, Excel

• Performed bounding box annotation on image and video datasets for object detection tasks
• Labeled objects with high accuracy by following project-specific guidelines and class definitions
• Maintained consistency across large datasets to ensure reliable AI model training
• Conducted quality checks and validation to identify and correct annotation errors
• Collaborated with team members to resolve ambiguities and improve labeling standards

Data Annotator — Multi-Modal AI Dataset - YO IT Consulting

(2023-09 - 2024-01)

Tools Used: Label Studio, Excel

• Annotated and categorized text and image datasets using predefined taxonomies and labeling guidelines
• Processed large volumes of data, converting unstructured inputs into structured and high-quality outputs
• Applied rubrics and classification standards to maintain consistency across annotation tasks
• Contributed to improving AI model accuracy and reliability through precise annotation work
• Managed tasks independently while ensuring timely delivery and consistent output quality

CSE(AIML) - Computer Science (AI/ML) - PRINCETON INSTITUTE OF ENGINEERING AND TECHNOLOGY (2022 - 2026)

Junior College - SHIVANI JUNIOR COLLEGE (2020 - 2022)

Secondary School - Z P P SECONDARY SCHOOL (2019 - 2020)