AI Data Quality Reviewer

Job Overview

We are seeking a detail-oriented AI Data Quality Reviewer to help ensure the quality, accuracy, and integrity of data used in AI training and evaluation projects. In this role, you will review contributor submissions across text and video formats, assess them against project-specific guidelines, and make consistent quality decisions at scale.

The ideal candidate has experience working in high-volume review environments, possesses exceptional attention to detail, and can apply detailed guidelines consistently while maintaining productivity targets. You will play a critical role in maintaining dataset quality, identifying suspicious or low-quality submissions, and providing clear feedback to contributors.

Core Tasks:

• Review contributor submissions across text and video against project-specific guidelines and acceptance criteria
• Approve, reject, or return submissions for correction while providing clear and feedback
• Maintain high accuracy and consistency while meeting project throughput and turnaround-time targets
• Identify duplicate, low-effort, synthetic, manipulated, or otherwise suspicious submissions and escalate potential integrity issues
• Apply detailed review rubrics consistently across large volumes of submissions
• Track recurring contributor errors and flag unclear or ineffective task instructions
• Accurately record review decisions, rejection reasons, and other required information

Must Have:

• 1-3+ years of experience in data annotation, quality assurance, content moderation, trust & safety, document review, or another high-volume review environment
• Experience reviewing the work or submissions of other people against defined guidelines, policies, rubrics, or SOPs
• Exceptional attention to detail and ability to identify subtle errors, inconsistencies, and quality issues
• Strong judgment and ability to make consistent decisions when reviewing large volumes of submissions
• Ability to quickly learn and accurately apply new project-specific guidelines and acceptance criteria
• Strong (C-level) written and verbal English communication skills
• Ability to provide concise, clear, and constructive reviewer feedback
• Comfortable working toward measurable accuracy, productivity, and turnaround targets
• Strong organizational skills and the ability to accurately document review decisions
• Ability to work full-time EST hours

Nice to Have:

• Previous experience reviewing AI training data, data annotations, RLHF tasks, or human-generated datasets
• Background in content moderation, trust & safety, fraud detection, data integrity, or marketplace quality control

Originally posted on Himalayas