Remote Data Labeling Specialist

Remote Data Labeling Jobs in Canada (Full Time)

Rex.zone supports AI/ML training pipelines through data labeling, RLHF evaluation, prompt evaluation, and QA checks. You will apply annotation guidelines compliance to improve training data quality for large language models and computer vision systems.

• Produce accurate labels for NLP and computer vision tasks
• Perform RLHF ranking and pairwise preference judgments for LLM training
• Execute prompt evaluation and rubric-based scoring for model outputs
• Apply named entity recognition and taxonomy tagging
• Complete content safety labeling with clear rationales
• Run QA evaluation workflows including audits, cross-checks, and error analysis
• Track annotation guidelines compliance and propose guideline improvements
• Escalate ambiguous cases and contribute to calibration sessions that improve inter-annotator agreement

• Professional experience in data labeling, data annotation, QA evaluation, or trust and safety
• Strong attention to detail and ability to follow annotation guidelines
• Comfortable working with web-based annotation tools and spreadsheets
• Ability to explain decisions clearly using rubrics, rationales, and examples
• Familiarity with NLP concepts such as named entity recognition and text classification
• Availability for full-time remote work with reliable connectivity

• Experience with RLHF workflows, LLM evaluation, and prompt evaluation
• Exposure to computer vision annotation (bounding boxes, polygons, segmentation masks, keypoints)
• Understanding of training data quality metrics (accuracy, consistency, coverage, bias)
• Prior work with content safety labeling and policy interpretation
• Experience collaborating with AI labs, tech startups, BPOs, or annotation vendors

You may use labeling platforms, internal QA dashboards, and guideline repositories. Workflows can include gold-standard calibration, blind reviews, inter-annotator agreement checks, and structured error analysis aimed at model performance improvement for production AI systems.