Generative AI Analyst - USA (Remote)

Welo Global

4d•Remote

About The Position

We are hiring full-time Generative AI Analysts in the United States to support evaluation and quality review of AI-generated videos. In this role, you will review text prompts, watch corresponding video outputs, and identify mismatches, inconsistencies, and visual errors. This role is best suited for candidates with strong attention to detail, excellent visual comprehension, and the ability to follow structured guidelines consistently. Candidates should be comfortable reviewing video content, comparing visual outputs against written prompts, and writing clear, concise annotations. A solid understanding of US driving and road rules is especially important, as some tasks may involve roadway scenarios, vehicle behavior, and basic robotics behavior in real-world environments.

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, with the ability to describe errors clearly and concisely.
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.

Nice To Haves

Prior experience evaluating AI-generated video, synthetic media, autonomous driving data, robotics scenarios, or traffic-related visual content.
Familiarity with US traffic rules, road signage, lane behavior, vehicle interactions, pedestrian behavior, and common driving scenarios.
Experience with QA, audit, or second-pass review workflows, including calibration, sampling, defect tracking, or error taxonomy development.
Ability to identify recurring model failure patterns across tasks or batches.

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, rather than the full sentence unless needed.
Add visual or behavioral errors as annotation instances in annotation platform.
Write brief, clear descriptions for each error instance.
Avoid duplicate annotations by ensuring errors already captured as prompt mismatches are not added again as separate instances.
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.
Identify recurring or systematic errors across tasks and document examples for review.
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.
Incorporate feedback from quality reviews into subsequent work.
Support throughput and quality targets while maintaining accuracy at scale.