Data Annotation Remote Jobs

Data annotation specialist is a search-recognizable role that labels and evaluates data powering AI/ML training at scale. On Rex.zone, you’ll work across RLHF (Reinforcement Learning from Human Feedback), data labeling, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling to improve training data quality and model performance. Apply for remote, contract, freelance, and full-time openings with AI labs, tech startups, BPOs, and annotation vendors. Join LLM training pipelines, ensure annotation guidelines compliance, and deliver measurable model performance improvement through rigorous evaluation and feedback loops—all through Rex.zone.

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Key Responsibilities

• Produce high-quality labels for NLP, computer vision, and speech datasets, adhering to annotation guidelines compliance and quality thresholds. • Execute RLHF and prompt evaluation tasks (pairwise preference, scoring rubrics, safety/harms checks) to drive model performance improvement. • Perform NER, sentiment, intent, taxonomy/ontology mapping, and content safety labeling (PII, toxicity, bias, misinformation). • Conduct computer vision annotation: bounding boxes, polygons, keypoints, semantic/instance segmentation, and video event labeling. • Run QA evaluation: inter-annotator agreement checks, gold set validation, error taxonomies, and calibration sessions. • Maintain training data quality with sampling, spot checks, and issue triage in Jira/Asana. • Document edge cases, update label schemas, and collaborate with ML engineers on feedback cycles.

Required Qualifications

• Experience in data labeling or QA evaluation for AI/ML datasets (entry-level welcome; senior roles require 2–5+ years). • Strong attention to detail, reading comprehension, and consistency under clear SLAs. • Familiarity with LLM evaluation tasks (pairwise preference, scoring prompts), basic ML metrics (precision, recall, F1), and inter-annotator agreement (Cohen’s kappa). • Domain literacy in NLP or computer vision annotation; ability to follow evolving guidelines. • Excellent written English; multilingual skills are a plus.

Preferred Skills

• Experience with RLHF data generation, red teaming, safety taxonomies, and prompt engineering. • Knowledge of ontology design, label schema versioning, and dataset governance. • Understanding of active learning, human-in-the-loop, and evaluation harnesses. • Basic scripting for data ops (CSV/JSON hygiene) is a plus.

Tools and Stack

• Labeling: Label Studio, Prodigy, Scale AI, SuperAnnotate, CVAT, SageMaker Ground Truth. • Collaboration: Jira, Notion, Confluence, Slack. • Versioning/Storage: DVC, git, data lakes. • Evaluation: custom LLM judges, pairwise preference UIs, rubric-based scoring forms.

Workflows You’ll Join

• LLM training pipelines: data collection → annotation → RLHF preference → safety review → model eval → iteration. • Computer vision labeling sprints with QA gates and ground-truth audits. • Content safety labeling for policy compliance and risk mitigation. • Continuous quality improvement via gold sets, spot checks, and calibration.

Employment Types and Modifiers

Remote-first roles with options for full-time, part-time, contract, freelance, and temporary. Entry-level to senior tracks available across NLP, computer vision, content safety, and LLM training. Employers include AI labs, tech startups, BPOs, and annotation vendors.

Compensation and Benefits

Competitive hourly rates or salaries depending on seniority and domain complexity, with performance-based bonuses tied to training data quality and delivery SLAs. Some roles include benefits, equipment stipends, and flexible schedules across time zones.

How to Apply on Rex.zone

Create your profile on Rex.zone, highlight domain expertise (NLP, CV, safety), and include sample projects demonstrating annotation guidelines compliance and QA evidence. Complete skill checks (NER, prompt evaluation, CV tasks) to qualify faster for remote openings.

Quick Answers

  • Q: Do I need ML coding experience?

    No, but basic familiarity with datasets, CSV/JSON hygiene, and evaluation concepts helps you progress faster.

  • Q: What time zones are supported?

    Global. Many projects are async with optional overlap for QA reviews and calibration sessions.

  • Q: Is training provided?

    Most roles include onboarding with guidelines, gold sets, and calibration tasks before production work.

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

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Ready to Shape the Future of Data Annotation & Labeling?

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