Remote Data Labeling Specialist (Raleigh)

Rex.zone; Raleigh (NC); Remote; USD 41,328 - 68,880; Full time

Job summary

Rex.zone is seeking a Remote Data Labeling Specialist to work from anywhere within the United States. You will label and review multi-modal data for AI training, including text, images, audio, and video, and perform NLP tasks such as classification and named entity recognition.

The role also covers computer vision annotation with bounding boxes and segmentation, content safety labeling, and RLHF-style evaluation tasks.

Qualifications

• 2+ years in data labeling, data annotation, QA evaluation, or AI data operations.
• Strong attention to detail and proven annotation guidelines compliance.
• Comfortable making consistent decisions across edge cases (mid-senior expectations).
• Experience with RLHF-style ranking, LLM evaluation, or prompt evaluation preferred.

Responsibilities

• Deliver accurate labels aligned to annotation guidelines and complex rubrics.
• Execute QA evaluation workflows (spot checks, gold set validation, sampling audits, inter-annotator agreement).
• Document edge cases, rationales, and disagreement resolution to improve training data quality.
• Maintain throughput targets while preserving precision and consistency across batches.
• Protect data privacy and follow content and safety policies.

Skills

Attention to detail

Data labeling

QA evaluation

RLHF ranking

Job description

Overview

Rex.zone is hiring a Remote Data Labeling Specialist aligned to Raleigh-based job seekers. Work is performed remotely within the US. You will produce and verify high-quality labeled datasets used to train and evaluate AI models in real products, supporting LLM training pipelines and evaluation loops.

What You Will Work On

• Label and review multi-modal data (text, images, audio, video) for AI training and evaluation


• Complete NLP tasks such as classification and named entity recognition (NER)


• Perform computer vision annotation including bounding boxes and segmentation


• Support content safety labeling and policy-aligned decisions


• Conduct LLM evaluation tasks such as RLHF preference ranking and prompt evaluation

Key Responsibilities

• Deliver accurate labels aligned to annotation guidelines and complex rubrics


• Execute QA evaluation workflows (spot checks, gold set validation, sampling audits, inter-annotator agreement)


• Document edge cases, rationales, and disagreement resolution to improve training data quality


• Maintain throughput targets while preserving precision and consistency across batches


• Protect data privacy and follow content and safety policies

Required Qualifications

• 2+ years in data labeling, data annotation, QA evaluation, or AI data operations


• Strong attention to detail and proven annotation guidelines compliance


• Comfortable making consistent decisions across edge cases (mid-senior expectations)


• Experience with RLHF-style ranking, LLM evaluation, or prompt evaluation preferred

Compensation

$30–$50 per hour (base pay; varies by project and scope).