Remote Data Labeling Specialist (Vancouver)
<strong>Remote Data Labeling Specialist (Vancouver) — Full-Time<br><br></strong>Rex.zone is hiring a Remote Data Labeling Specialist to deliver consistent, policy-aligned annotations used to train and evaluate AI/ML models. You will work across NLP labeling, RLHF preference ranking, prompt evaluation, computer vision annotation, and content safety labeling to improve training data quality and downstream model performance.<br><br><strong>Key Responsibilities<br><br></strong><ul><li>Apply annotation guidelines accurately across NLP and computer vision tasks</li><li>Perform RLHF preference ranking and rubric-based evaluations to align model behavior with human preferences</li><li>Execute prompt evaluation and response quality scoring for LLM evaluation workflows</li><li>Conduct QA evaluation, sampling audits, guideline compliance checks, and error categorization to reduce label noise</li><li>Label content safety categories (e.g., harassment, self-harm, hate) using policy taxonomies</li><li>Collaborate with project leads to resolve edge cases, refine rubrics, and document decisions</li><li>Track productivity and accuracy metrics to support model performance improvement<br><br></li></ul><strong>Workstreams You May Support<br><br></strong><ul><li>NLP data labeling: named entity recognition (NER), intent classification, sentiment/topic labeling, summarization evaluation</li><li>LLM training pipelines: instruction-following evaluation, pairwise preference ranking, rubric grading</li><li>Computer vision annotation: bounding boxes, polygons, keypoints, segmentation, OCR validation</li><li>Content safety labeling: policy-based moderation labels and severity scoring</li><li>Multimodal tasks: text-image relevance, caption validation, VQA-style evaluation<br><br></li></ul><strong>Required Qualifications<br><br></strong><ul><li>Experience applying structured guidelines to data annotation and/or QA evaluation work</li><li>Strong written communication for consistent labeling rationale and disagreement resolution</li><li>Comfort working with ambiguity, edge cases, and evolving rubrics</li><li>Familiarity with NLP, RLHF, or LLM evaluation concepts (training data quality, preference ranking, prompt evaluation)</li><li>Ability to maintain accuracy at production scale and meet full-time delivery expectations<br><br></li></ul><strong>Preferred Qualifications<br><br></strong><ul><li>Experience with annotation platforms and audit workflows</li><li>Exposure to computer vision annotation tools (boxes, polygons, segmentation)</li><li>Experience with content safety labeling or policy taxonomy interpretation</li><li>Experience documenting guidelines, building QA checklists, or running inter-annotator agreement checks<br><br></li></ul><strong>Remote Work Notes<br><br></strong>This is a <strong>Remote</strong> role. You can be based in Vancouver while working with distributed teams. Projects may require overlap with US business hours, and task availability can vary by domain.<br><br><strong>Pay:</strong> $30–$50 per hour (base salary).
