We are building a careful, dependable team for annotation, review, and project support. If you enjoy structured work and want to contribute to AI systems, we would like to hear from you.
Start a Client ProjectBengal, India | Official connection: sumanasanaroy@gmail.com | LinkedIn
Annotiq AI welcomes careful, curious people who enjoy detail-oriented work. Annotation is not just clicking boxes; it is reading instructions, noticing patterns, asking good questions, and helping AI systems learn from cleaner examples.
Support image, text, document, and video labeling projects from your own workspace with clear task instructions and review feedback.
Help compare completed labels with guidelines, catch inconsistencies, and explain corrections in a way that improves the next batch.
Guide task flow, track delivery, prepare notes for clients, and keep annotation teams aligned with updated project instructions.
The best people for annotation work are patient, consistent, and honest when something is unclear. We value communication, reliability, and the ability to follow detailed instructions without losing the bigger picture.
Comfortable working with spreadsheets, web tools, images, documents, and simple dashboards.
Able to follow detailed guidelines and flag examples that do not fit neatly.
Interested in AI, machine learning data, and flexible remote work.
Scroll through short moving previews with animated label boxes, giving visitors a clearer feel for object review, frame tracking, and quality checking.
Moving frames can be checked with bounding boxes, labels, and reviewer notes before they are used for model training.
Teams can track objects across frames, tag actions, and prepare structured data for computer vision projects.
Reviewers compare edge cases, correct inconsistent labels, and keep datasets useful for real AI systems.