Remote Data Labeling Jobs in Boston

Rex.zone; Boston (MA); Remote; USD 41,000 - 69,000; Full time

Job summary

Rex.zone is hiring for a full-time, fully remote data labeling role based in the United States. You will label text, images, audio, and video, following strict guidelines to improve AI training data quality for LLM pipelines.

Work fully remotely from the US with an hourly pay range and strong emphasis on QA, RLHF tasks, and consistency checks. This position requires independent work in a remote setting while meeting quality and throughput goals.

Qualifications

• Mid-Senior experience delivering accurate annotations at production scale.
• Strong attention to detail and ability to follow strict taxonomies and policy requirements.
• Comfort working independently in a remote, full-time setting while meeting quality and throughput goals.
• Understanding of how labeling decisions impact model performance and downstream metrics.

Responsibilities

• Annotate text, image, audio, and video samples for AI/ML datasets.
• Perform QA evaluations, self-audits, and consistency checks.
• Complete RLHF tasks such as ranking and rubric-based scoring with concise rationales.
• Run prompt evaluation for usefulness, harmlessness, and factuality.
• Label NER and relations for NLP tasks.
• Support computer vision annotation (bounding boxes, polygons) where applicable.
• Apply content safety labeling policies and elevate edge cases with examples.
• Document decision rules to resolve ambiguity and improve batch consistency.

Skills

Annotation accuracy

Attention to detail

Remote work

Quality assurance

Job description

Remote Data Labeling Jobs in Boston (Remote, US)

Rex.zone is hiring for a full-time, fully remote role focused on creating and evaluating high-quality training data for AI/ML systems. You will label text, images, audio, and video while following strict annotation guidelines compliance to improve training data quality for LLM training pipelines.

What You Will Do

• Annotate and label text/image/audio/video samples for AI/ML datasets
• Perform QA evaluation, self-audits, and consistency checks (gold tasks, audits, inter-annotator agreement)
• Complete RLHF tasks such as pairwise preference ranking and rubric-based scoring with concise rationales
• Run prompt evaluation for helpfulness, harmlessness, and factuality to support large language model evaluation
• Label named entity recognition (NER) and relations for NLP tasks
• Support computer vision annotation (bounding boxes, polygons, segmentation/keypoints) where applicable
• Apply content safety labeling policies and elevate edge cases with clear examples
• Document decision rules to resolve ambiguity and improve batch-to-batch consistency

What We Are Looking For

• Mid-Senior experience delivering accurate annotations at production scale
• Strong attention to detail and ability to follow strict taxonomies and policy requirements
• Comfort working independently in a remote, full-time setting while meeting quality and throughput goals
• Understanding of how labeling decisions impact model performance improvement and downstream metrics

Location & Remote Notes

This role is listed for Boston search intent; work is performed remotely within the US with reliable internet and secure workspace practices.

Compensation

Hourly base pay range: $30-$50 per hour (based on skills alignment, dataset domain complexity, and QA evaluation performance).