Data Annotation Jobs (Remote)

Data annotation jobs (remote) on Rex.zone connect skilled raters and labelers with AI/ML training workflows. As a data annotation specialist, you’ll create and evaluate training data for RLHF, data labeling, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling. Your work powers LLM training pipelines and model performance improvement through training data quality and annotation guidelines compliance. On our platform, you’ll complete tasks like large language model evaluation, QA review, and dataset curation for AI labs, tech startups, BPOs, and annotation vendors. Explore full-time, contract, and freelance roles, from entry-level to senior lead, and apply to remote projects that fit your domain expertise in NLP, vision, and speech.

Key Responsibilities

Produce accurate labels across text, image, audio, and video; perform RLHF judgments and LLM prompt evaluation; execute named entity recognition (NER), sentiment, toxicity and content safety labeling; create bounding boxes, polygons, keypoints, and segmentation masks for computer vision annotation; validate training data quality through QA evaluation and spot-checks; ensure annotation guidelines compliance; document edge cases and propose taxonomy updates; collaborate with leads to drive model performance improvement and dataset curation.

Required Qualifications

Strong attention to detail and consistency; fluent written English; ability to follow complex annotation guidelines; basic understanding of AI/ML concepts and the impact of human-in-the-loop workflows; reliable internet and computer; familiarity with productivity tools; capacity to meet throughput and quality SLAs; comfort with repetitive tasks while maintaining accuracy.

Preferred Skills

Experience with LLM evaluation and RLHF rater workflows; prior data labeling on platforms such as Labelbox, Scale, SuperAnnotate, or CVAT; knowledge of NLP labeling (NER, sentiment, intent); computer vision annotation (bounding box, segmentation); content safety and policy enforcement; basic Python or SQL for data review; understanding of inter-annotator agreement, gold sets, and quality metrics.

Domains You May Work In

NLP: NER, summarization, sentiment, intent classification, prompt evaluation. Computer Vision: object detection, instance/semantic segmentation, OCR, pose/keypoints. Speech/Audio: transcription, diarization, tagging, classification. Trust & Safety: content policy labeling, safety category tagging. LLM Training: preference ranking, large language model evaluation, instruction tuning data creation.

Quality and Compliance

Follow annotation guidelines precisely; maintain high inter-annotator agreement; leverage calibration tasks and gold-standard checks; document conflicts and escalate ambiguities; align with privacy and data handling policies; contribute to continuous improvement for annotation guidelines compliance and training data quality.

Employment Types and Schedules

Remote opportunities across full-time, part-time, contract, temporary, and freelance engagements. Openings available for entry-level labelers to senior QA leads and project managers. Work with AI labs, tech startups, BPOs, and annotation vendors on hourly, task-based, or milestone contracts.

Tools & Platforms

Rex.zone project hub plus industry-standard tools such as Labelbox, Scale, SuperAnnotate, CVAT, LightTag, Prodigy, and custom LLM eval dashboards. Use metrics like precision/recall, throughput targets, quality scores, and agreement rates to drive model performance improvement.

Why Work via Rex.zone

Discover curated, verified projects that directly impact AI/ML training. Match with roles by domain expertise and level, track quality metrics, and build a portfolio that showcases measurable gains in model performance. Transparent workflows, clear guidelines, and timely payouts.

How to Apply

Create your Rex.zone profile, complete skill checks (NLP, vision, content safety), pass a short calibration task, and choose remote projects by schedule and domain. Senior candidates can apply for QA lead and guideline author roles.

Role Q&A

Q: What does a remote data annotation specialist do day to day?
You label text, images, audio, or video, complete RLHF and LLM prompt evaluations, run QA checks, and ensure annotation guidelines compliance to improve training data quality.
Q: How does this work impact AI/ML models?
High-quality annotations feed LLM training pipelines and computer vision models, enabling measurable model performance improvement and safer, more accurate outputs.
Q: Which industries hire for these roles?
AI labs, tech startups, BPOs, and annotation vendors across domains like NLP, computer vision, speech, and content safety.
Q: Are there opportunities for advancement?
Yes. Progress from entry-level annotator to senior annotator, QA reviewer, guideline author, and project/QA lead.
Q: What schedules are available?
Remote roles include full-time, part-time, contract, temporary, and freelance options with flexible hours.
Q: Do I need prior experience?
Not always. Entry-level roles provide training and calibration tasks; senior roles require proven accuracy and domain experience.

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50+Countries Represented

Industry-Leading Compensation

We believe exceptional intelligence deserves exceptional pay. Our platform consistently offers rates above the industry average, rewarding experts for their true value and real impact on frontier AI. Here, your expertise isn't just appreciated—it's properly compensated.

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No office. No commute. No constraints. Our fully remote workflow gives experts complete flexibility to work at their own pace, from any country, any time zone. You focus on meaningful tasks—we handle the rest.

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