Generative AI Analyst
New
Remote within the United StatesFull-TimeMiddle
Salary28.8 USD per hour
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Job Details
- Languages
- English
- Required Skills
- Generative AIComputer Vision
Requirements
- Experience in video annotation, multimedia annotation, content quality review, data labeling, computer vision labeling, Generative AI evaluation, or a closely related field.
- Strong attention to detail and ability to identify subtle errors, mismatches, and inconsistencies between prompts and videos.
- Solid understanding of US driving rules, road behavior, traffic scenarios, and roadway conventions.
- Good reading comprehension and ability to accurately compare written prompts against visual outputs.
- Strong written communication skills in English.
- Ability to follow detailed guidelines consistently and maintain high accuracy across repetitive tasks.
- Critical thinking and sound judgment when reviewing ambiguous or complex scenarios.
- Basic understanding of robotics behavior in real-world environments.
- Comfortable working in structured annotation platforms or similar tools.
- Ability to maintain focus and quality while reviewing multimedia content for extended periods.
Responsibilities
- Review text prompts and corresponding AI-generated video clips to identify mismatches, inconsistencies, and visual errors.
- Tag specific parts of the prompt that do not match the video by identifying only the incorrect prompt text.
- Add visual or behavioral errors as annotation instances in annotation platform.
- Write brief, clear descriptions for each error instance.
- Evaluate video content for actions, context, motion, scene consistency, object behavior, and prompt alignment.
- Apply project guidelines consistently across repetitive, detail-oriented tasks.
- Use critical thinking and judgment to handle ambiguous scenarios and determine the most accurate ground truth.
- Perform self-QA on completed work and correct errors before submission.
- Participate in calibration sessions to align interpretation of guidelines and reduce annotator-to-annotator variance.
- Support throughput and quality targets while maintaining accuracy at scale.
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