tezzo mummo

I’m a detail-oriented Computer Vision and Data Annotation Specialist with over 2 years of hands-on experience in image analysis, dataset labeling, and machine learning support. I focus on identifying fine-grained visual differences and applying precise annotation techniques to improve model performance.

Since Jan 2023, I’ve worked as a Computer Vision Data Annotator (Freelance / Remote), annotating and reviewing thousands of images for object detection, classification, and segmentation. I use Labelbox, CVAT, V7, and Supervisely to build high-quality labeled datasets and maintain consistency through quality checks and validation.

I’m especially strong at edge case identification and handling ambiguous data, so the datasets stay reliable and help models generalize better. I also follow detailed annotation guidelines and collaborate with distributed teams to keep annotation workflows accurate and efficient.

Before that, I gained practical experience as an AIDataAnnotationIntern (Jun 2022–Dec 2022), supporting computer vision model training with image classification and bounding box annotation. I’m currently building deeper expertise through my Bachelor’s Degree in Computer Science (Kenyatta University) with coursework in Artificial Intelligence, Machine Learning, and Computer Vision.