Data Annotation Specialist (Computer Vision) Offline

We are seeking a detail-oriented and reliable Data Annotation Specialist to support computer vision projects by accurately labeling and annotating image and video datasets. The ideal candidate will have experience working with common annotation tools and a basic understanding of computer vision concepts.


Key Responsibilities:
• Annotate images and videos with:
• Bounding boxes
• Classification labels
• Segmentation masks / polygons
• Keypoints for pose estimation
• Follow detailed guidelines and class structures to ensure consistency and accuracy.
• Maintain high levels of annotation quality, with attention to edge cases and ambiguous scenarios.
• Potentially assist in Video Quality Assurance (QA) tasks in the future, verifying and validating outputs from machine learning models.
• Work with various labeling platforms such as Roboflow, CVAT, or other internal/custom tools.
• Communicate clearly with project managers or ML engineers to resolve uncertainties in annotation guidelines.


Required Qualifications:
• Experience with at least one annotation tool (e.g., CVAT, Roboflow, Labelbox, Supervisely, etc.)
• Understanding of basic image and video annotation concepts.
• High attention to detail and a structured approach to data tasks.
• Ability to follow instructions and class guidelines with consistency.


Preferred Qualifications:
• Prior experience annotating data for computer vision tasks (detection, segmentation, pose estimation).
• Familiarity with ML datasets (e.g., COCO format).
• Ability to work independently and meet project deadlines.
• Experience with video annotation and frame-by-frame labeling is a plus.


Nice to Have:
• Basic Python skills or experience working with Jupyter notebooks.
• Previous work on ML projects or QA tasks related to computer vision.