AI Data Labeling Jobs at Rex.zone connect skilled annotators with LLM training pipelines, RLHF projects, and enterprise AI workflows. As a data annotation specialist, you ensure training data quality, annotation guidelines compliance, and model performance improvement across NLP, computer vision, and content safety tasks. Work includes prompt evaluation, named entity recognition, computer vision annotation, and large language model evaluation for QA. The intent is clear: join Rex.zone to label, review, and curate datasets used in real-world machine learning systems for AI labs, tech startups, and annotation vendors. Explore remote, contract, freelance, and full-time roles designed for entry-level to senior contributors who improve dataset fidelity and accelerate safe, reliable AI.
This role is a recognized search entity: AI data labeling expert / data annotation specialist. You will annotate, validate, and audit datasets powering LLMs and ML models. Typical projects include RLHF preference ranking, prompt evaluation, named entity recognition for NLP, computer vision annotation (bounding boxes, polygons, segmentation), content safety labeling, and multilingual text classification, all aligned to rigorous guidelines on Rex.zone.
Hiring for remote, contract, freelance, and full-time positions spanning entry-level to senior levels. Domain focus areas include NLP, computer vision, content safety, speech/audio, and LLM training. Common titles: Data Annotation Specialist, AI Data Labeling Expert, QA Rater, Prompt Evaluator, Safety Rater, NER Annotator, CV Labeler.
Apply annotation guidelines with high precision, perform QA evaluation and error analysis, execute prompt evaluation and RLHF preference judgments, conduct large language model evaluation, and enforce dataset taxonomies. Drive training data quality, annotation guidelines compliance, and model performance improvement by identifying edge cases, ambiguities, and adversarial examples.
Strong attention to detail, consistency under guidelines, and familiarity with labeling taxonomies. Experience with NER, text classification, sentiment, intent detection, CV tasks (bounding boxes, landmarks, segmentation), and content safety policies. Comfortable with spreadsheets/CSV, regex basics, and annotation platforms. Bonus: bilingual proficiency, domain expertise (medical, legal), and RLHF evaluation experience.
Projects follow auditable workflows on Rex.zone: instruction review, pilot labels, inter-annotator agreement checks, conflict resolution, and QA sign-off. You will use annotation dashboards, review queues, and analytics that surface precision/recall, agreement scores, and issue trends to streamline large language model evaluation and continuous dataset improvement.
You will collaborate with AI labs refining LLMs, tech startups building data pipelines, BPOs scaling annotation teams, and specialized annotation vendors. Rex.zone routes qualified talent to organizations needing dependable labeling capacity for NLP, computer vision, and content safety programs.
Competitive rates based on task complexity and seniority. Opportunities include per-task contracts, hourly freelance, and salaried full-time roles. Senior roles may lead guideline design, QA audits, and workforce training. Remote-first teams with flexible schedules and region-friendly compliance through Rex.zone.
Create a talent profile on Rex.zone, list domain strengths (NLP, CV, content safety, LLM training), and complete a skills assessment. When matched, you will receive project briefs and pilot tasks. Apply now to explore active AI data labeling jobs and join RLHF and evaluation pipelines that ship real-world AI.
Progress from entry-level annotator to senior QA lead, guideline author, or labeling operations manager. Build expertise in training data quality, annotation guidelines compliance, and model performance improvement while contributing to safe, robust AI systems through Rex.zone.
It involves annotating and validating datasets used to train and evaluate ML models and LLMs. Tasks include RLHF preference ranking, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling, all under clear guidelines.
Yes. Rex.zone lists remote, contract, freelance, and full-time jobs across time zones. Many teams operate asynchronously with defined QA checkpoints and review cycles.
Entry-level roles are available with training on guidelines and tools. Prior experience in NLP, computer vision, content safety, or LLM evaluation helps, particularly for senior and QA-focused positions.
You will work in Rex.zone-managed workflows and standard annotation platforms. Expect dashboards for task queues, QA review, inter-annotator agreement, and error analysis that support large language model evaluation.
Quality is tracked via inter-annotator agreement, precision/recall on gold standards, guideline adherence scores, and QA evaluation audits. Feedback loops continuously improve training data quality.
Common domains include NLP (NER, intent, sentiment), computer vision (detection, segmentation), content safety (policy labeling), audio/speech, and RLHF prompt evaluation for LLM training pipelines.
Rex.zone connects you with AI labs, tech startups, BPOs, and annotation vendors seeking reliable labeling capacity and QA specialists.
Create a profile on Rex.zone, complete the skills assessment, and select preferred modifiers (remote, contract, full-time, entry-level, senior). You will receive matches and pilot tasks for active projects.
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