Remote Data Labeling Specialist — AI Training Data QA & NER

Rex.zone; Milano; Remote; EUR 40,000 - 58,000; Full time

Benefits offered by this job

Remote work

Job summary

Rex.zone is hiring a Mid-Senior Data Labeling professional to produce and verify high-quality training data for AI systems. This is a fully remote, full-time role targeting candidates in Milan and similar locations, with job metadata listed under Country: US.

What you will do includes labeling data across text, images, audio, and video; performing LLM evaluation, prompt evaluation, and RLHF ranking; QA evaluation using rubrics; adhering to strict annotation guidelines; documenting edge cases;

Qualifications

• Mid-Senior experience in data labeling/annotation or ML QA evaluation.
• Strong attention to detail and comfort with quality-focused, repeatable workflows.
• Familiarity with LLM evaluation concepts (instruction-following, groundedness, safety).
• Ability to work independently in a remote full-time environment with throughput/quality targets.

Responsibilities

• Label and review training data across text, images, audio, and video
• Perform LLM evaluation, prompt evaluation, and RLHF preference ranking
• Execute QA evaluation using rubrics for accuracy, relevance, and safety
• Apply and maintain strict annotation guidelines compliance; document edge cases and decisions
• Run named entity recognition (NER) and taxonomy/tagging workflows
• Support computer vision annotation (e.g., boxes/polygons/segmentation) and content safety labeling
• Report dataset issues, ambiguities, and recurring failure patterns to improve training data quality

Skills

Data labeling

LLM evaluation concepts

Attention to detail

Remote work

Job description

Rex.zone is hiring a Mid-Senior Data Labeling professional to produce and verify high-quality training data for AI systems. This is a fully remote, full-time role targeting candidates in Milan and similar locations, with job metadata listed under Country: US.

What you will do includes labeling data across text, images, audio, and video; performing LLM evaluation, prompt evaluation, and RLHF ranking; QA evaluation using rubrics; adhering to strict annotation guidelines; documenting edge cases;