Data Labeling Jobs from Home

Data Labeling Jobs from Home on Rex.zone connect skilled annotators to real AI/ML training workflows. This role entity spans data labeling, RLHF (Reinforcement Learning from Human Feedback), QA evaluation, prompt evaluation, named entity recognition (NER), computer vision annotation, and content safety labeling. Remote labelers improve training data quality and model performance for large language models and vision systems by following annotation guidelines and SOPs. Apply to remote, contract, freelance, full-time, and part-time openings from AI labs, tech startups, BPOs, and annotation vendors via Rex.zone. Projects include NLP, computer vision, and multimodal tasks across LLM training pipelines.

Key Responsibilities

Execute consistent data labeling across NLP, computer vision, and multimodal tasks; apply RLHF criteria to score and rank model outputs; perform QA evaluation, spot checks, and inter-annotator agreement reviews; follow annotation guidelines and taxonomies with high precision; conduct prompt evaluation for LLMs and document qualitative feedback; identify edge cases, bias, and ambiguity; flag content safety risks and enforce policy; improve training data quality through audits, error analysis, and feedback; collaborate with leads to refine guidelines; meet throughput and quality SLAs while working remotely.

Required Qualifications

Proven attention to detail and consistency; familiarity with NLP concepts (NER, sentiment, intent) and computer vision labeling (bounding boxes, polygons, keypoints); ability to follow SOPs and annotation guidelines; strong reading comprehension and written communication; experience with labeling tools (Label Studio, Prodigy, CVAT or similar); comfort with quality metrics (precision/recall, IAA); reliability in remote settings with stable internet; commitment to data privacy and content safety policies.

Preferred Experience

Background in LLM evaluation or RLHF workflows; taxonomy and ontology design; multilingual annotation; exposure to dataset curation, de-duplication, and bias analysis; prompt engineering basics; understanding of model performance improvement loops; using issue trackers (Jira) and collaboration tools (Slack); familiarity with version control and task queues; prior work with AI labs, tech startups, BPOs, or annotation vendors.

Work Arrangements

Openings include remote, contract, freelance, full-time, part-time, and temporary engagements; roles from entry-level to senior QA/reviewer; global opportunities with flexible schedules; project-based pay or hourly rates depending on scope; clear SLAs, NDAs, and compliance requirements; advancement paths into lead annotator, QA specialist, or guideline designer roles.

Tools & Workflow

Use industry-standard tools (Label Studio, Prodigy, CVAT, internal labeling UIs) with detailed instructions and examples; access project-specific annotation guidelines and policy documents; follow multi-step QA pipelines and feedback loops; contribute to continuous improvement via error reports and guideline refinements; work within LLM training pipelines to evaluate outputs, rate responses, and capture structured rationales.

About Rex.zone

Rex.zone is an AI training platform connecting annotators with AI labs, startups, and vendors. We provide verified projects, clear guidelines, and support for NLP, computer vision, content safety, and RLHF tasks. Join to help elevate training data quality and accelerate model performance improvement in production systems.

How to Apply

Create a Rex.zone profile, complete a quick skills check, and select projects aligned to your domain expertise (NLP, CV, content safety, RLHF). Submit your application for remote roles—entry-level, senior, freelance, or full-time—and start contributing to high-impact AI/ML training pipelines.

Application & Process

Q: What are typical pay rates?
Rates vary by domain and complexity: entry-level tasks pay per item or hourly; RLHF and senior QA roles pay higher. Exact rates are listed per project on Rex.zone.
Q: What are the technical requirements?
Stable internet, modern browser, and a computer capable of running web labeling tools. For CV tasks, a larger screen and mouse are recommended.
Q: Do I need to sign an NDA?
Most projects require NDAs and adherence to privacy and content handling policies, especially for sensitive or safety-related data.
Q: Can I work multiple projects?
Yes. You can join multiple projects if you meet quality standards and availability requirements. Manage schedules to maintain SLA compliance.
Q: How are promotions handled?
Consistent quality and throughput can lead to reviewer or lead annotator roles, with responsibilities in guideline design and QA management.

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