Data Annotator, Data Analyst for computer vision

I lead a team of 7 including dedicated QA reviewers and trained annotators helping AI and Machine Learning teams turn raw images and video into clean, model-ready training data through accurate data annotation, data labeling, and dataset preparation for computer vision projects, from small pilot batches to large-scale production datasets.
Core Services

Image Annotation: bounding boxes, polygon & semantic segmentation, instance segmentation, keypoints/landmarks

Video Annotation: frame-by-frame labeling, object tracking, multi-object tracking

Text Annotation: classification, NLP tagging, entity labeling
Object Detection & Classification: custom model training support (YOLO)

Dataset QA & Validation: accuracy review, consistency checks, error correction
Format Delivery: COCO, YOLO, Pascal VOC, JSON, CSV matched to your pipeline

Tools & Platforms
CVAT, Roboflow, Label Studio, LabelImg, LabelMe plus custom annotation tools when a project needs a tailored workflow.
How My Team Works

My team of 7 annotators and QA reviewers follows a structured internal QA pass before anything reaches you; every batch is reviewed for accuracy and consistency before final delivery. As the lead, I personally review tool setup, labeling guidelines, and edge cases so quality stays consistent even at volume.

Beyond Annotation
I also have hands-on Machine Learning and Computer Vision experience (TensorFlow, PyTorch, YOLO, model training and evaluation), so I understand how labeling decisions affect downstream model performance not just "the labeling," but the data that actually makes your model work.

If you need reliable image, video, or text annotation for a computer vision or ML project send an invite and let's talk about your dataset.