Remote Data Labeling Jobs Milan

Rex.zone; Milano; A distancia; EUR 40.000 - 58.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

Descripción de la vacante

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;

Formación

• 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.

Responsabilidades

• 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

Conocimientos

Data labeling

LLM evaluation concepts

Attention to detail

Remote work

Descripción del empleo

Remote Data Labeling Jobs (Milan)

Rex.zone is hiring a

Remote Data Labeling Jobs (Milan)

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 searching in Milan and similar locations), while job metadata remains listed under Country: US.

What You Will Do

• 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

Required 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

Assessment

Hiring assessments may cover guideline compliance, edge-case reasoning, QA accuracy, RLHF ranking, prompt evaluation, and basic tagging such as NER.

High-quality labeled data directly improves model training signals and downstream performance.