Remote Data Labeling Jobs in Madrid

Rex.zone; Madrid; A distancia; EUR 26.000 - 38.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Fully remote

Asynchronous collaboration

Descripción de la vacante

Rex.zone is hiring for a full-time, fully remote data labeling role focused on training-data creation and quality control for AI/ML systems. You will label and evaluate text, images, audio, and conversations used in LLM evaluation and computer vision annotation workflows, improving training data quality, annotation consistency, and model performance.

This remote position emphasizes asynchronous collaboration across data ops, QA, and project leads.

Formación

• Mid-Senior experience in data labeling or data annotation operations.
• Strong attention to detail and ability to follow structured rubrics and guidelines.
• Familiarity with NLP concepts (classification, NER, sentiment) and LLM training pipelines.
• Ability to explain labeling decisions clearly and maintain consistent quality under deadlines.

Responsabilidades

• Label and evaluate text, images, audio, and conversations for AI/ML systems.
• Improve training data quality and annotation consistency.
• Contribute to LLM evaluation and CV annotation workflows.
• Attend to content safety labeling and edge-case documentation.
• Collaborate asynchronously with data ops, QA, and project leads.

Conocimientos

Data labeling

NLP concepts

Quality control

Explain decisions

Descripción del empleo

Remote Data Labeling Jobs in Madrid (Fully Remote)

Rex.zone is hiring for a full-time, fully remote data labeling role focused on training-data creation and quality control for AI/ML systems. You will label and evaluate text, images, audio, and conversations used in large language model evaluation and computer vision annotation workflows, improving training data quality, annotation consistency, and model performance.

What You’ll Work On

• Text labeling for NLP tasks (classification, NER, summarization) and rubric-based decision making
• Prompt evaluation and LLM response scoring (helpfulness/harmlessness/honesty)
• RLHF-style preference ranking and pairwise judgments
• QA evaluation using checklists, sampling plans, spot checks, and gold tasks
• Computer vision annotation support (bounding boxes, polygons, keypoints) as needed
• Content safety labeling to ensure policy-compliant outputs
• Document edge cases, track error patterns, and propose guideline/rubric improvements
• Asynchronous collaboration with data ops, QA, and project leads in a remote workflow

Required Qualifications

• Mid-Senior experience in data labeling or data annotation operations
• Strong attention to detail and ability to follow structured rubrics and guidelines
• Familiarity with NLP concepts (classification, NER, sentiment) and LLM training pipelines
• Ability to explain labeling decisions clearly and maintain consistent quality under deadlines

Preferred

• Experience with RLHF, large language model evaluation, and audit-ready QA workflows
• Exposure to computer vision annotation formats and inter-annotator agreement methods
• Background supporting AI labs, tech startups, BPOs, or annotation vendors

Employment Details

Workplace: Remote (asynchronous collaboration). Employment Type: FULL_TIME. This role aligns to Madrid job-search intent for remote opportunities while operating fully online.