Job Description
Note: The job is a remote job and is open to candidates in USA. Rex.zone is hiring for remote, full-time AI Data Labeling roles focused on training data creation and evaluation workflows for AI/ML systems. The role involves supporting LLM training pipelines and multimodal model development through consistent labeling and review.
Responsibilities
- Label text, image, and/or multimodal data following detailed annotation guidelines
- Perform RLHF tasks such as preference ranking and helpfulness/harmlessness evaluations
- Execute QA evaluation (spot checks, consensus review, error categorization) to improve training data quality
- Conduct prompt evaluation and rubric-based scoring for instruction tuning and LLM evaluation
- Document edge cases, propose clarifications, and contribute to feedback loops that improve model performance
- Support NLP labeling (intent, sentiment, toxicity, topic, summarization quality)
- Perform named entity recognition and entity linking
- Conduct content safety labeling for policy compliance and risk mitigation
- Perform computer vision annotation (bounding boxes, polygons, keypoints)
- Conduct grounding checks, reasoning quality ratings, and refusal/safety assessments
Skills
- Experience in data annotation or QA evaluation in production workflows
- Strong annotation guideline compliance, accuracy, and consistency
- Comfort with structured labeling schemas and rubric-based scoring
- Ability to work independently in a remote environment and meet throughput targets
- Exposure to RLHF, prompt evaluation, LLM evaluation, NER, content safety, or computer vision annotation
- Familiarity with inter-annotator agreement, sampling-based QA, audits, and error analysis
Company Overview
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