[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-remote-ai-data-labeling-jobs":3},{"Slug":4,"Header":5,"Ques":36,"job_category":48},"remote-ai-data-labeling-jobs",{"desc":6,"title":7,"content":8},"Remote AI Data Labeling Jobs at Rex.zone connect skilled annotators with AI labs, tech startups, BPOs, and annotation vendors building production LLM and computer vision systems. These roles power the AI\u002FML training pipeline: data labeling, QA evaluation, prompt evaluation, RLHF (Reinforcement Learning from Human Feedback), named entity recognition, computer vision annotation, and content safety labeling to improve model performance. Work across NLP and vision tasks with clear annotation guidelines, emphasizing training data quality, annotation guidelines compliance, and large language model evaluation. Apply for freelance, contract, part-time, or full-time openings globally. Start entry-level or grow to senior QA lead and drive model performance improvement on the Rex.zone AI\u002FML training platform.","Remote AI Data Labeling Jobs",[9,12,15,18,21,24,27,30,33],{"h2":10,"desc":11},"Key Responsibilities","Annotate text, image, audio, and video data for NLP and computer vision tasks; execute RLHF comparisons and preference ranking; perform prompt evaluation and judge LLM outputs for correctness, safety, and style; conduct content safety labeling and policy application; run named entity recognition (NER), sentiment, intent, and topic tagging; create and follow detailed annotation guidelines; perform QA evaluation, gold set creation, and spot checks; document edge cases and escalate ambiguity; collaborate with model trainers to improve training data quality and model performance; contribute to large language model evaluation studies and A\u002FB tests.",{"h2":13,"desc":14},"Required Qualifications","Fluent written English and strong reading comprehension; meticulous attention to detail; ability to learn and apply evolving labeling taxonomies; proven consistency and throughput in repetitive tasks; familiarity with annotation guidelines and annotation guidelines compliance; reliable internet and remote work setup; availability for scheduled sprints. For content safety roles: resilience and adherence to safety policies. For computer vision: basic understanding of bounding boxes, polygons, and keypoints.",{"h2":16,"desc":17},"Preferred Experience","Experience with data annotation platforms (e.g., Label Studio, Prodigy, SuperAnnotate); prior work in LLM evaluation, RLHF preference labeling, or human feedback loops; background in linguistics, psychology, library science, information retrieval, or QA; domain expertise in healthcare, finance, legal, or e-commerce taxonomies; experience as a QA lead or reviewer; familiarity with prompt engineering and systematic error analysis.",{"h2":19,"desc":20},"Tools and Platforms","Annotation tools: Label Studio, Scale-style interfaces, SuperAnnotate; Issue tracking: Jira, Notion; Productivity: Google Workspace, spreadsheets; Communication: Slack; Optional technical skills: basic Python for data inspection, regex for text normalization. All work is coordinated via the Rex.zone AI training and workforce platform.",{"h2":22,"desc":23},"Projects and Domains","NLP: chat moderation, summarization, reasoning, NER, sentiment, intent, classification; LLM training: RLHF preference ranking, instruction tuning, large language model evaluation; Computer vision: object detection, segmentation, OCR; Content safety: policy labeling, toxicity, misinformation, age appropriateness; Multilingual tasks where available.",{"h2":25,"desc":26},"Work Arrangements & Compensation","Remote-first roles across time zones; openings include freelance, contract, part-time, and full-time; both entry-level and senior QA\u002Freviewer tracks; pay structured per-task, per-hour, or per-sprint depending on project; opportunities with AI labs, tech startups, BPOs, and annotation vendors; consistent performance can lead to reviewer and QA lead roles.",{"h2":28,"desc":29},"How to Apply on Rex.zone","Create a Rex.zone profile; complete a short skills check covering guidelines comprehension and sample annotations; indicate your availability and domains (NLP, computer vision, content safety); match with live projects; receive onboarding, annotation guidelines, and pay details; start contributing to model performance improvement.",{"h2":31,"desc":32},"Career Growth","Advance from labeler to reviewer, QA lead, and project coordinator; specialize in complex domains (medical, legal) or RLHF judgment; develop expertise in prompt evaluation, guideline design, and gold set curation; contribute feedback to improve labeling taxonomies and training pipelines.",{"h2":34,"desc":35},"About Rex.zone","Rex.zone is an AI\u002FML training platform connecting global annotators with organizations that need trustworthy training data. We focus on quality, throughput, and auditability to help teams ship safer, higher-performing models.",{"title":37,"content":38},"Quick Questions",[39,42,45],{"A":40,"Q":41},"AI labs, tech startups, BPOs, and annotation vendors seeking reliable training data operations.","Who hires through Rex.zone?",{"A":43,"Q":44},"Detail orientation, guideline mastery, QA evaluation, and LLM output judgment for safety and correctness.","What skills are most valuable?",{"A":46,"Q":47},"Yes—remote contract, freelance, part-time, and full-time projects are available year-round.","Can I work part-time or freelance?","Remote Data Labeling & Annotation"]