AI Data Labeling Remote Jobs

Rex.zone is recruiting AI Data Labeling talent for remote roles across NLP, computer vision, and content safety. As an AI data annotation specialist, you will create and evaluate training data that powers LLM training pipelines, RLHF (Reinforcement Learning from Human Feedback), prompt evaluation, named entity recognition, computer vision annotation, and safety/quality review. These roles are central to training data quality, annotation guidelines compliance, and model performance improvement through large language model evaluation and QA workflows. Join AI labs, tech startups, BPOs, and annotation vendors through Rex.zone to contribute to real-world AI/ML training at scale.

Key Responsibilities

Produce high-quality annotations for NLP (NER, sentiment, classification), LLM evaluation (pairwise ranking, preference labeling, prompt evaluation), computer vision (bounding boxes, polygons, keypoints), ASR/audio tagging, and content safety labeling. Follow annotation guidelines, taxonomy definitions, and edge-case policies to ensure training data quality. Perform QA evaluation with consensus checks, spot audits, and adjudication. Provide structured feedback to improve guidelines and enable model performance improvement. Support RLHF and alignment tasks by scoring outputs and documenting reasoning traces.

Required Qualifications

Proven attention to detail, reliability, and consistency under production deadlines. Strong reading comprehension and communication in English; multilingual skills are a plus. Familiarity with annotation tools (e.g., Labelbox, Prodigy, Scale, CVAT, LightTag, SuperAnnotate). Ability to interpret labeling taxonomies, handle ambiguity, and apply annotation guidelines compliance. Comfort with productivity tooling (Google Sheets, Jira, Confluence) and basic quality metrics such as inter-annotator agreement (IAA).

Preferred Skills

Experience with LLM evaluation tasks, RLHF preference labeling, prompt engineering basics, and red-teaming for content safety. Domain expertise in at least one area: healthcare, finance, e-commerce, legal, or media. Basic technical fluency (regex, CSV hygiene, simple Python for data review) is helpful but not required. Understanding of dataset curation, sampling strategies, and bias/coverage considerations in AI/ML training.

Workflows and Tools

Collaborate within a structured LLM training pipeline: data sourcing, pilot labeling, calibration, production labeling, QA sampling, and continuous improvement. Use labeling platforms (Labelbox, Scale, CVAT, SuperAnnotate, Prodigy) and evaluation frameworks for large language model evaluation and content safety scoring. Participate in feedback loops with QA reviewers and project leads to tighten guidelines and raise training data quality.

Roles, Employment Types, and Domains

Multiple openings across remote, contract, freelance, part-time, and full-time tracks, from entry-level to senior reviewer/lead. Domain focuses include NLP, computer vision, content safety, and LLM training/evaluation. Employers range from AI labs and tech startups to BPOs and specialized annotation vendors. Compensation varies by project complexity, language expertise, and employment type.

Impact and Growth

Your annotations directly inform model behavior, enabling safer, more capable AI. High performers can progress into QA lead, guideline designer, data operations, and evaluation specialist roles. You will gain deep exposure to production AI/ML workflows and best practices for scalable annotation.

How to Apply

Explore open AI data labeling remote roles and apply via Rex.zone. Submit a concise resume highlighting domain expertise, languages, and tooling. Include examples of annotation work or QA projects if available. Qualified candidates may be invited to complete calibration tasks and sample assessments.

About Rex.zone

Rex.zone connects skilled annotators and evaluators with AI labs, startups, BPOs, and annotation vendors. We focus on high-signal work in RLHF, LLM evaluation, computer vision, NLP, and content safety. Join us to shape the next generation of AI through quality training data.

AI Data Labeling Remote Jobs: FAQs

Q: What does an AI data labeler do?
AI data labelers annotate text, images, audio, and video, evaluate LLM outputs, and perform QA to create high-quality training datasets that improve model performance.
Q: Is this fully remote?
Yes. Most roles are remote with flexible schedules; some projects may prefer specific time zones for collaboration and QA handoffs.
Q: What tools will I use?
Common tools include Labelbox, Scale, CVAT, SuperAnnotate, Prodigy, and internal dashboards for guideline review, sampling, and QA evaluation.
Q: Are there entry-level and senior openings?
Yes. Entry-level roles focus on consistent production annotation; senior roles include QA lead, adjudication, and guideline design.
Q: How do I stand out as a candidate?
Show strong attention to detail, demonstrate familiarity with guidelines, provide examples, and highlight domain or language expertise relevant to the project.
Q: What is RLHF and how does it relate?
RLHF uses human preference judgments on model outputs to align LLM behavior. Labelers rank outputs, provide rationales, and help train reward models.
Q: What domains are hiring?
NLP, computer vision, and content safety across industries such as e-commerce, finance, healthcare, and media. Employers include AI labs, startups, BPOs, and vendors.
Q: What quality standards are expected?
High inter-annotator agreement, adherence to annotation guidelines, thorough edge-case handling, and reliable turnaround times.

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.

Respect at the Core of Everything

AI trainers are the heart of our company. We treat every expert with trust, humanity, and genuine appreciation. From personalized support to transparent communication, we build long-term relationships rooted in respect and care.

Ready to Shape the Future of Data Annotation & Evaluation?

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