Senior Data Annotation Specialist

I believed that my previous work experienced as a product researcher helps me to improved more skills and knowledge.

Labeling elements of data (images, videos, text, or any other format) by adding contextual information which ML models can learn from. specialized in Lidar 3d annotation, image annotation, 2d 3d segmentation, polyline annotation, video box annotation and keypoint annotation with different platforms like Remotasks, Kognic, V7labs, Encord, Dataloop, Amazon sagemaker and LDP.

I have extensive experience in data annotation across image, video, and LiDAR datasets, supporting the development of AI and machine learning models. My work involves accurately labeling data using bounding boxes, semantic segmentation, polyline annotation, and object classification, while strictly following detailed annotation guidelines. I have performed frame-by-frame video annotation, ensuring temporal consistency and precise object tracking. I also have experience working with geospatial data, annotating road elements, infrastructure, and other map-related features with high accuracy. I am proficient in using multiple annotation platforms including CVAT, V7, Supervisely, Amazon SageMaker, Remotasks, Kognic, and UAI. Through these tools, I have handled large-scale datasets, maintaining both speed and quality to meet project targets. In addition to annotation, I have contributed to quality assurance and review processes by identifying errors, handling edge cases, and ensuring consistency across datasets. I have also supported team members by clarifying guidelines and maintaining high annotation standards. Overall, my experience has helped me develop strong attention to detail, consistency, and the ability to deliver high-quality annotated data essential for training reliable AI models.