What are the responsibilities and job description for the Remote Data Labeling Jobs in Boston position at Rex.zone?
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
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).
How To Apply
Apply through Rex.zone by submitting your resume and a brief summary of your data labeling, RLHF, prompt evaluation, and QA evaluation experience, including any specialization in NLP, computer vision annotation, or content safety labeling.
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 escalate edge cases with clear examples
- Document decision rules to resolve ambiguity and improve batch-to-batch consistency
- 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
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).
How To Apply
Apply through Rex.zone by submitting your resume and a brief summary of your data labeling, RLHF, prompt evaluation, and QA evaluation experience, including any specialization in NLP, computer vision annotation, or content safety labeling.
Salary : $30 - $50