In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Responsibilities
Review short video and audio clips, scrutinizing both visual and auditory elements for detailed annotation and assessment.
Evaluate the accuracy of AI-generated descriptions, verifying alignment with provided guidelines and identifying inconsistencies or errors.
Deliver clear, concise written feedback to highlight inaccuracies, ambiguities, or areas of uncertainty in the reviewed content.
Apply consistent judgment to ensure that content labeling supports robust AI evaluation and training objectives.
Flag content that does not meet specified standards or requires further clarification from project leads.
Collaborate with project coordinators and follow project protocols to maintain high annotation quality and data integrity.
Contribute to continual process improvement by suggesting annotation and quality assurance enhancements.
Preferred skills
Demonstrated experience in data annotation, labeling, or content moderation — particularly with video or audio data.
Keen attention to detail and the ability to apply consistent, objective judgment throughout repetitive tasks.
Familiarity with generalist training, content review, or guideline-based evaluation is advantageous.
Comfort working independently and reliably in a remote project setting.
Adaptability to quickly learn new annotation tools, protocols, and quality standards.
Commitment to upholding data confidentiality and accuracy throughout the engagement.
Language requirements
Strong English communication skills, with the ability to provide detailed written and verbal feedback.
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.
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