Data Labeling Jobs from Home is a remote-friendly job entity for data annotation specialists who label text, images, audio, and video to power AI/ML training pipelines. On Rex.zone, you can apply to roles spanning RLHF (Reinforcement Learning from Human Feedback), named entity recognition, computer vision annotation, content safety labeling, prompt evaluation, and QA evaluation. The intent is to produce high-quality training data that improves model performance, supports large language model evaluation, and ensures annotation guidelines compliance. Whether you seek freelance, contract, or full-time opportunities, Rex.zone connects you with AI labs, tech startups, BPOs, and annotation vendors running scalable workflows in NLP, computer vision, and LLM training.
Work from home to label and review multimodal data that trains and evaluates AI systems. Tasks include text tagging for NLP, named entity recognition, conversation and prompt evaluation for LLMs, RLHF preference ranking, image/video bounding boxes and polygons for computer vision, audio transcription, and content safety labeling. You will follow annotation guidelines, contribute to training data quality, and help drive model performance improvement across production ML pipelines.
Execute precise annotations per project specs; perform QA evaluation and consensus checks; flag edge cases and ambiguous samples; maintain annotation guidelines compliance; curate and validate datasets; participate in large language model evaluation and prompt scoring; document decisions and taxonomy changes; collaborate with leads on labeling workflows, audits, and inter-annotator agreement.
Strong attention to detail, reading comprehension, and consistency; familiarity with NLP, computer vision annotation, and content safety concepts; ability to follow detailed instructions; basic understanding of LLM training pipelines and RLHF; comfort with labeling tools (Label Studio, Prodigy, SuperAnnotate, LightTag or similar); reliable remote setup; for senior roles, experience in guideline creation, QA processes, and dataset curation.
You may work across taxonomy design, schema mapping, ontology updates, prompt evaluation rubrics, preference ranking frameworks, red-teaming for safety, and test-set creation. Projects use web-based platforms, versioned guidelines, audit trails, and quality metrics such as accuracy, precision/recall, inter-annotator agreement, consensus scoring, and sampling-based QC.
Remote roles available as freelance, contract, or full-time; entry-level and senior openings. Flexible schedules, project-based assignments, and shift options across time zones. Employers include AI labs, tech startups, BPOs, and annotation vendors. Domains span NLP, computer vision, content safety, and LLM training.
Pay varies by project complexity and seniority, with hourly and per-task rates. Senior contributors may receive bonuses for QA leadership, guideline development, or throughput and quality targets. Exact compensation is specified per posting on Rex.zone.
Create your candidate profile on Rex.zone, browse Data Labeling Jobs from Home, filter by remote, contract, freelance, or full-time roles, and submit an application. Complete any required sample tasks and guideline quizzes, then track interviews and onboarding through your Rex.zone dashboard.
It is a remote role where you annotate and review text, images, audio, or video to build training datasets for AI/ML workflows, including LLM evaluation, RLHF, and computer vision tasks.
Entry-level roles are available. Experience with annotation tools and following detailed guidelines helps. Senior roles require proven QA, guideline design, and dataset curation experience.
Projects commonly use platforms like Label Studio, Prodigy, SuperAnnotate, LightTag or vendor-specific tools, along with QA dashboards tracking accuracy and inter-annotator agreement.
Quality is tracked through annotation guidelines compliance, training data quality metrics, consensus scoring, audit sampling, and model performance improvement signals on evaluation sets.
Most projects include onboarding materials and guideline walkthroughs. Some offer paid sample tasks or short quizzes before full assignment access.
Flexible remote schedules are common. Roles include freelance, contract, and full-time options with shift coverage across time zones.
AI labs, tech startups, BPOs, and annotation vendors hire data labelers for NLP, computer vision, content safety, and LLM training pipelines.
Sign up on Rex.zone, upload your profile, browse data labeling postings, and submit applications. Complete any sample tasks and monitor your status through your Rex.zone dashboard.
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