Entry-Level Data Labeling Jobs

Entry-level data labeling jobs at Rex.zone connect early-career annotators to AI labs, tech startups, BPOs, and annotation vendors powering LLM training pipelines. As a data labeling specialist, you tag text, images, audio, and video to enhance training data quality, ensure annotation guidelines compliance, and support model performance improvement through RLHF, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling. This role is central to large language model evaluation and supervised fine-tuning in real-world AI/ML workflows. Explore remote, contract, freelance, and full-time openings on Rex.zone across NLP, computer vision, and safety. Our platform provides training, tooling, and standardized guidelines to help new labelers succeed and deliver production-ready datasets.

About the Role

Entry-level data labelers at Rex.zone prepare, annotate, and review datasets used to train and evaluate machine learning systems. Day-to-day work includes reading task instructions, labeling examples, verifying quality, and contributing feedback to improve guidelines. Projects span NLP (NER, sentiment, summarization), computer vision (bounding boxes, polygons, segmentation), and content safety labeling (policy compliance checks). Workflows align with LLM training pipelines (SFT and RLHF), where careful labeling enables prompt evaluation, QA evaluation, and large language model evaluation.

Key Responsibilities

Apply annotation guidelines accurately; label text, images, audio, and video at scale; perform QA checks to improve training data quality; follow escalation paths for ambiguous cases; provide structured feedback to enhance annotation guidelines compliance; collaborate with leads on inter-annotator agreement; support model performance improvement by resolving edge cases and adding high-signal examples; contribute to RLHF and prompt evaluation tasks; document issues in tooling and maintain labeling throughput targets.

Required Skills

Strong attention to detail; clear written communication; ability to follow instructions precisely; familiarity with basic ML data concepts; comfort using tools like Label Studio, Prodigy, CVAT, SuperAnnotate, Doccano, spreadsheets, and JSON; reliability in meeting throughput/quality quotas; ethical judgment for content safety labeling; reading comprehension in English; eagerness to learn workflows for named entity recognition, computer vision annotation, and RLHF prompt rating.

Job Types & Modifiers

Roles include remote, contract, freelance, full-time, and pathways to senior positions. Projects cover NLP, computer vision, content safety, and LLM training. Employers hiring through Rex.zone include AI labs, tech startups, BPOs, and specialized annotation vendors. Entry-level candidates can start immediately; experienced annotators can join senior and QA lead tracks.

Workflow & Tools

Typical steps: task intake, instruction review, sample labeling, production labeling, QA evaluation, consensus comparison, and dataset handoff. Tools may include Label Studio, CVAT, Doccano, Prodigy, SuperAnnotate, internal Rex.zone tooling, and standard formats like JSON/CSV. Quality metrics focus on accuracy, consistency, inter-annotator agreement, and error analysis to support large language model evaluation and model performance improvement.

Compensation & Benefits

Competitive hourly or per-task rates, paid onboarding for select projects, flexible scheduling, and performance-based bonuses on qualifying engagements. Compensation varies by project complexity (NLP, computer vision annotation, content safety), employer type (AI labs, tech startups, BPOs, annotation vendors), and contract length (freelance, short-term contract, full-time).

Career Growth

Advance from entry-level labeler to senior labeler, QA reviewer, domain specialist (NER, vision, safety), RLHF rater, prompt evaluation specialist, or project lead. Rex.zone offers training paths, calibrated rubrics, and mentorship to elevate annotation quality and expand responsibilities across LLM training pipelines.

How to Apply on Rex.zone

Create a Rex.zone profile, complete a short skills assessment, verify identity (where required), and select projects aligned with your availability and domain interests. Submit applications to remote, contract, freelance, or full-time postings and start labeling after passing guideline comprehension and trial tasks.

Frequently Asked Questions

Q: What is an entry-level data labeling job?
It involves annotating text, images, audio, and video to create high-quality datasets for AI/ML training and evaluation. Work centers on training data quality, annotation guidelines compliance, and tasks like NER, bounding boxes, sentiment, and content safety.
Q: Do I need prior AI experience?
No. Rex.zone provides onboarding, clear instructions, and calibration tasks. Attention to detail, reliability, and strong reading comprehension are more important than prior ML expertise.
Q: Is the work remote?
Yes. Many projects on Rex.zone are remote and offer contract, freelance, and full-time options. Time zones and availability windows may apply depending on the employer.
Q: How is quality measured?
Quality is tracked using accuracy scores, inter-annotator agreement, guideline adherence, and QA evaluation results. Feedback loops and calibration tasks help maintain consistency and model performance improvement.
Q: What domains can I work in?
Common domains include NLP (named entity recognition, sentiment, summarization), computer vision annotation (bounding boxes, polygons, segmentation), content safety labeling (policy checks), and LLM training tasks such as RLHF and prompt evaluation.
Q: What tools will I use?
Projects may use Label Studio, CVAT, Doccano, Prodigy, SuperAnnotate, internal Rex.zone tools, spreadsheets, and JSON/CSV formats. Tooling depends on the employer and project type.
Q: What is RLHF and how does it relate to labeling?
RLHF (Reinforcement Learning from Human Feedback) uses human judgments to compare or rate model outputs. Entry-level raters help evaluate prompts and responses, supporting large language model evaluation and fine-tuning.
Q: How do I apply on Rex.zone?
Sign up, complete the skills assessment, choose projects, and submit applications. After passing trial tasks and guideline checks, you can begin labeling.

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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