Remote Data Labeling Jobs

Remote Data Labeling Jobs on Rex.zone connect data annotation specialists with AI labs, tech startups, BPOs, and annotation vendors building LLM training pipelines. This job entity covers RLHF, data labeling, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling. Applicants help improve training data quality, enforce annotation guidelines compliance, and drive model performance improvement through large language model evaluation and dataset curation. Roles span NLP, vision, and multimodal tasks, integrating into real-world machine learning workflows via structured guidelines, tools, and feedback loops. Explore open roles, apply to projects, and track assignments through Rex.zone’s curated marketplace designed for remote, contract, freelance, and full-time opportunities across entry-level to senior tiers.

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About the Role

As a remote data labeling professional on Rex.zone, you create high-quality training datasets that power machine learning and large language models. Workstreams span text, images, audio, video, and multimodal inputs, including RLHF evaluations, prompt rating, NER tagging, computer vision bounding boxes, and content safety assessments.

Key Responsibilities

Follow annotation guidelines compliance, execute labeling workflows, perform QA evaluation, conduct prompt evaluation and LLM output reviews, deliver named entity recognition, taxonomy mapping, and ontology alignment. Maintain training data quality through audits, gold tasks, and inter-annotator agreement, enabling model performance improvement and reliable large language model evaluation.

Required Skills

Strong attention to detail, reading comprehension, and consistency. Familiarity with NLP, computer vision, and content safety concepts. Comfort with JSON, CSV, and basic spreadsheets; experience with tools like Label Studio, CVAT, Prodigy, Doccano, LightTag, or SuperAnnotate. Understanding of privacy, ethics, and secure data handling; ability to follow structured instructions and provide clear feedback.

Employment Types & Domains

Opportunities include remote, contract, freelance, and full-time roles, from entry-level to senior. Domain coverage spans NLP, computer vision, speech, multimodal data, content safety, and LLM training pipelines. Employers include AI labs, tech startups, BPOs, and specialized annotation vendors sourcing projects through Rex.zone.

Tools & Workflow

Use standardized labeling platforms, task queues, and review stages. Apply guidelines, edge-case notes, and calibration sessions to reduce variance. Submit structured annotations with metadata, confidence scores, and rationales; participate in feedback loops that link labeling decisions to downstream model training and evaluation.

Quality & Compliance

Quality is measured via inter-annotator agreement, precision/recall on gold sets, error taxonomies, and audit sampling. Compliance includes adherence to instructions, privacy rules, content safety policies, and domain-specific regulations. Rex.zone enforces quality gates to ensure training data integrity.

Compensation

Rates vary by domain, complexity, and seniority. Projects may pay per task, per hour, or per milestone. Competitive compensation is offered by AI labs, tech startups, BPOs, and annotation vendors; see individual listings on Rex.zone for exact terms and eligibility.

Application Process

Create your profile on Rex.zone, indicate domain skills, take calibration tests, and complete sample tasks. Qualified candidates are matched to live projects with clear scopes, timelines, and onboarding materials. Accepted contributors receive ongoing assignments and performance feedback.

Growth Path

Advance from entry-level labeler to senior reviewer, quality lead, or domain specialist (NLP, CV, content safety). Experienced contributors can transition into annotation operations, project management, guideline authoring, and RLHF evaluation roles supporting LLM training.

Location & Work Hours

Fully remote with flexible schedules and timezone coverage. Some projects require overlap for standups or reviews; most tasks can be completed asynchronously within defined SLAs and delivery windows.

Frequently Asked Questions

  • Q: What is a remote data labeling job?

    It is a role where you annotate and evaluate datasets from home to train and validate AI systems, including tasks like NER, computer vision annotation, content safety labeling, and RLHF or prompt evaluation for LLMs.

  • Q: Which domains are available on Rex.zone?

    Domains include NLP, computer vision, speech, multimodal data, content safety, and large language model evaluation, with projects from AI labs, tech startups, BPOs, and annotation vendors.

  • Q: What tools will I use?

    Projects may use Label Studio, CVAT, Prodigy, Doccano, LightTag, SuperAnnotate, or vendor-specific platforms. You will submit structured outputs (JSON/CSV) and follow standardized guidelines.

  • Q: Are these roles truly remote?

    Yes. Rex.zone curates fully remote opportunities. Some projects request limited timezone overlap for reviews or standups; most work is asynchronous.

  • Q: What experience do I need?

    Entry-level roles require attention to detail and instruction following. Senior roles expect domain expertise, prior QA evaluation experience, guideline authoring, and ability to mentor reviewers.

  • Q: How is quality measured?

    Through gold tasks, inter-annotator agreement, audit checks, and error taxonomy reporting. Consistent training data quality and annotation guidelines compliance are required.

  • Q: How does RLHF fit into labeling?

    RLHF tasks involve ranking or scoring model outputs, comparing responses against policy and preference criteria, and providing structured feedback that improves LLM behavior.

  • Q: What contract types are offered?

    Roles span contract, freelance, and full-time placements, with entry-level and senior tracks. Payment can be per task, hourly, or milestone-based depending on the project.

  • Q: How do I apply?

    Create a Rex.zone profile, pass calibration tests, and complete sample tasks. Once approved, you can apply to live postings and be matched to suitable projects.

  • Q: Is training provided?

    Yes. Most projects include onboarding guides, policy documents, and calibration tasks to align on definitions, edge cases, and quality expectations.

230+Domains Covered
120K+PhD, Specialist, Experts Onboarded
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.

Work Remotely, Work Freely

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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