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Remote Data Annotation Specialist (San Diego)

Remote Data Annotation Jobs In San Diego — Role Overview Rex.zone is hiring a Remote Data Annotation Specialist to create and evaluate labeled datasets that train and validate modern AI/ML systems. You will work across NLP labeling, computer vision annotation, RLHF preference ranking, and prompt-response evaluation while following versioned guidelines and meeting clear quality targets. What You Will Do <ul><li>Execute data labeling tasks across NLP and computer vision annotation projects (text span labeling, classification, bounding boxes, segmentation, attribute tagging).</li><li>Perform RLHF and large language model evaluation by ranking outputs, scoring prompt-response pairs, and identifying instruction-following failures.</li><li>Run QA evaluation workflows including self-checks, peer reviews, and gold-standard audits to improve training data quality and consistency.</li><li>Apply content safety labeling taxonomies and escalate uncertain cases using defined escalation paths.</li><li>Write clear rationales, document edge cases, and propose guideline updates when recurring ambiguities appear.</li><li>Track throughput and quality metrics (accuracy, agreement rates, defect density) to support model performance improvement. </li></ul>Required Qualifications <ul><li>Mid-Senior experience in data annotation, data labeling, QA evaluation, or LLM evaluation in production or vendor environments.</li><li>Strong reading comprehension and attention to detail for rubric-based judgment and policy-based labeling.</li><li>Comfort with annotation tools, task queues, and strict annotation guidelines compliance.</li><li>Ability to explain decisions with concise written rationales.</li><li>Familiarity with NLP concepts such as named entity recognition and taxonomy-driven labeling (preferred). </li></ul>Work Arrangement This is a Remote, FULL_TIME role aligned to US-based projects. Collaboration is primarily asynchronous with periodic calibration and QA review sessions. Location reference: San Diego, CA, US.

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