Computer Vision QA Specialist
SpaceJobs.Now is free for job seekers. Some links here pay us: a staffing agency, shift app, training program, course or store may pay us when you join or buy through our link, and a job ad network pays us when you click or apply to a job it carries (we mark those as sponsored or say so beside Apply). A job whose link pays us can be shown higher in a list. None of this costs you anything or changes what you are paid, and no employer can buy a spot or a featured place here.
Open in 1 location
SuperAnnotate (SME) posts this job as separate openings, each with its own application: the team, schedule and pay can differ between them.
Bangladesh
1 openBangladesh (Remote) (opens in new tab)
Contract · Posted 1mo ago
India
1 openIndia (Remote) (opens in new tab)
Contract · Posted 1mo ago
About the job
In this hourly, remote contractor role, you will work as a Computer Vision QA Specialist to review image and video annotations for quality, accuracy, and guideline compliance. You will evaluate annotations such as bounding boxes, segmentation masks, polygons, keypoints, object classes, attributes, and video tracks, identifying missing, incorrect, inconsistent, or poorly placed annotations.
You will also make corrections when required, provide clear feedback on quality issues, and communicate unclear cases to the project team. This role requires strong attention to detail, consistency, and the ability to carefully follow detailed computer vision annotation guidelines.
This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your computer vision QA work directly helps improve the world’s premier AI models by ensuring that visual training data is accurate, complete, consistent, and aligned with project expectations.
Responsibilities
- Review annotation quality: Review image and video annotations for accuracy, completeness, consistency, and adherence to project guidelines.
- Check annotation outputs: Evaluate bounding boxes, classes, attributes, segmentation masks, polygons, keypoints, image labels, and video tracking outputs.
- Identify annotation errors: Spot missing objects, incorrect labels, inaccurate boundaries, poor box placement, inconsistent attributes, duplicate annotations, and unclear edge cases.
- Make corrections when required: Correct annotation issues according to project-specific instructions and quality standards.
- Provide clear feedback: Document quality issues clearly so annotators or project teams can understand what needs to be improved.
- Follow project guidelines: Apply detailed annotation rules consistently across tasks, including rules for occlusion, truncation, blur, small objects, overlapping objects, and ambiguous cases.
- Escalate unclear cases: Communicate questions or uncertain examples to the project team for clarification.
- Maintain consistent work quality: Complete assigned QA work reliably while maintaining accuracy, consistency, and expected productivity.
Requirements
- Previous experience with computer vision annotation, image annotation, video annotation, or annotation QA is preferred.
- Experience reviewing or creating annotations such as bounding boxes, polygons, segmentation masks, keypoints, object classes, attributes, image classification, or video object tracking.
- Strong attention to detail and ability to identify missing, incorrect, inconsistent, overlapping, mislabeled, or poorly placed annotations.
- Comfortable working with detailed annotation guidelines, edge-case rules, quality standards, and project-specific instructions.
- Ability to review image and video data consistently across large batches while maintaining accuracy and speed.
- Comfortable making corrections when required and explaining annotation errors clearly.
- Good professional proficiency in English to understand guidelines, communicate questions, and provide written feedback.
- Able to work independently in an hourly remote workflow and commit consistent working hours based on project needs.
- Prior experience with annotation platforms such as SuperAnnotate, Labelbox, CVAT, Scale, Appen, Remotasks, Toloka, or similar tools is preferred.
Skills
- Annotation QA
- Image Annotation
- Keypoints
- Object Detection
- English
- Computer Vision
- Bounding Boxes
- Segmentation
- Polygons
- Video Annotation
Where you can work from
This job is 100% remote, for applicants who live in Bangladesh and India.
From SuperAnnotate (SME)'s job posting for Bangladesh (Remote), checked 10 Nov 2026. The employer's own page is the final word on requirements and availability. This is work on AI systems for an AI company, not for a space employer: never share export-controlled or proprietary technical data in a task, an application or an interview.
About SuperAnnotate (SME)
SME Careers matches vetted subject-matter experts to managed AI-training projects, paid weekly.
How it pays: Weekly through Deel as an independent contractor: approved work from Monday to Sunday is paid the following Friday, usually arriving one to three days later. Hourly projects pay tracked active time only.
More open jobs at SuperAnnotate (SME)
More AI training jobs for engineers, scientists and software people
An engineer or scientist with deep expertise?
One profile for every employer here. Space companies and their recruiters ask us for people with a specific degree, clearance, specialty or location: add yours once, and when a job fits, we introduce you, only with your yes. Free.
SuperAnnotate (SME) openings, sent to you weekly
Each week we send the newest postings from SuperAnnotate (SME)'s own careers site, along with similar openings at other space employers. It costs nothing and you can stop anytime.