The selected professionals will be responsible for reviewing video annotations and performing quality assurance checks to ensure that the data meets project requirements and quality standards.
Benefits
Opportunity to work on cutting-edge AI projects.
Competitive compensation.
Flexible working hours and remote work environment.
Responsibilities
Review and QA video annotations according to project-specific guidelines.
Validate the accuracy, completeness, and consistency of annotated video data.
Identify, document, and correct annotation issues.
Assess whether videos and annotations meet the required quality standards.
Maintain a high level of attention to detail across a large volume of video content.
Provide clear feedback on recurring errors or unclear cases.
Follow established workflows and meet strict project deadlines.
Collaborate with the project team to resolve questions and improve annotation quality.
Required skills
Strong visual attention to detail and analytical skills.
Ability to consistently apply detailed quality guidelines.
Preferred skills
Previous experience with video-based data annotation or video QA is strongly preferred.
Prior experience with data annotation or labeling projects.
Experience and education
At least 3 years of experience in data annotation projects.
Experience reviewing, validating, or auditing annotated datasets.
Equipment requirements
Reliable internet connection and access to a suitable computer.
Assessment requirements
Shortlisted candidates will complete an assessment.
Once the assessment is cleared, candidates can start.
Schedule details
Availability to work on weekends when required due to tight project timelines.
Thriveth makes AI data-training work easier to find, understand, and navigate. We replace uncertainty with clear opportunities, realistic expectations, and insights from real application journeys.