Overview
Rex.zone is hiring for a remote, full-time AI data labeling role focused on producing and evaluating high-quality labeled training data for modern AI/ML systems, including LLM training pipelines, RLHF workflows, and computer vision annotation.
What You Will Do
- Label and review text, image, and multimodal datasets using project rubrics and taxonomies
- Perform QA evaluation, spot checks, calibration rounds, and adjudication to maintain training data quality
- Complete RLHF-style preference ranking, rubric-based scoring, and prompt-response grading
- Conduct prompt evaluation for helpfulness, correctness, and safety
- Apply named entity recognition (NER) tagging and other NLP labeling tasks
- Support content safety labeling and safety policy enforcement where required
- Document edge cases and propose guideline updates to improve annotation guidelines compliance
- Track error patterns and contribute to error analysis for model performance improvement
Required Qualifications
- Mid-Senior experience in data annotation, QA, evaluation, or AI/ML production operations
- Ability to follow detailed rubrics and deliver consistent labeling decisions at scale
- Familiarity with LLM evaluation concepts and training data quality practices
- Strong written communication for documenting decisions and QA findings
Work Arrangement
Remote, full-time. Work is delivered through Rex.zone project systems with asynchronous collaboration and periodic calibration.
Compensation
$30–$50 per hour (base pay; depends on project scope and complexity).
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This position is listed as full time and able to be worked remotely.