Junior AI Data Labeler & QA Specialist

Rex.zone; United States; On-site; USD 32,000 - 52,000; Full time

Job summary

Rex.zone is seeking detail-oriented data labeling professionals to join a team that labels and evaluates training data for AI/ML systems, including text, images, and multimodal tasks. You will follow strict guidelines, document rationales, and uphold throughput targets.

This role emphasizes accuracy, edge-case documentation, and willingness to learn new labeling tools and taxonomy updates as the project evolves.

Qualifications

• Comfort with detailed rules, annotation rubrics, and high-precision work.
• Strong written communication for documenting rationales and disagreements.
• Ability to learn new labeling tools and taxonomy updates quickly.
• Familiarity with annotation concepts (NER, CV annotation, RLHF) is helpful.

Responsibilities

• Perform data labeling and data annotation across NLP, computer vision, and multimodal datasets
• Apply annotation guidelines and document edge cases for adjudication
• Execute QA evaluation workflows (spot checks, consensus review, error categorization)
• Support RLHF by rating responses, ranking candidates, and flagging hallucinations or policy risks
• Conduct prompt evaluation and evaluation set curation to improve model performance
• Maintain throughput and accuracy targets while protecting sensitive data

Skills

Attention to detail

Precise annotation

Strong written communication

Tool learning agility

Job description

Rex.zone is seeking detail-oriented data labeling professionals to join a team that labels and evaluates training data for AI/ML systems, including text, images, and multimodal tasks. You will follow strict guidelines, document rationales, and uphold throughput targets.

This role emphasizes accuracy, edge-case documentation, and willingness to learn new labeling tools and taxonomy updates as the project evolves.