Remote Data Annotator Jobs in Phoenix

Rex.zone; Phoenix (AZ); Remote; USD 42,000 - 64,000; Full time

Job summary

Rex.zone is seeking a remote data annotator in Phoenix to produce high-quality training data for AI systems across NLP and computer vision. You will label text and image data, and participate in RLHF-style evaluations to help improve model outputs.

This full-time remote role welcomes US-based candidates, with a focus on accuracy, consistency, and adherence to annotation guidelines. Strong English skills and detail orientation are essential.

Qualifications

• Must have strong written English and attention to detail.
• Ability to follow complex guidelines and self-audit for accuracy.
• Experience with data labeling tools or QA processes is a plus.

Responsibilities

• Label data for NLP tasks including classification, NER, sentiment, and toxicity.
• Evaluate LLM outputs for relevance, factuality, completeness, and safety.
• Rank model outputs using RLHF-style preference comparisons.
• Annotate CV data with bounding boxes, polygons, keypoints, and segmentation.
• Conduct QA evaluations, audits, and support calibration sessions.
• Document edge cases and help maintain annotation guidelines.

Skills

Strong written English

Attention to detail

Ability to follow guidelines

Job description

About The Role

Remote data annotator jobs in Phoenix at Rex.zone focus on producing high-quality training data for AI systems across NLP, computer vision, and LLM training pipelines. You will perform data labeling, RLHF-based preference ranking, prompt evaluation, and QA evaluation to improve model performance and training data quality.

What You Will Do

• Label data for NLP tasks such as text classification, intent, sentiment, toxicity, and named entity recognition
• Perform large language model evaluation by scoring relevance, factuality, completeness, instruction-following, and safety
• Execute RLHF-style preference ranking by comparing and ranking model outputs
• Annotate computer vision data using bounding boxes, polygons, keypoints, and segmentation
• Complete QA evaluation using audits, inter-annotator agreement targets, and rework when needed
• Follow annotation guidelines compliance, document edge cases, and support calibration sessions

Requirements

• Strong written English and attention to detail
• Ability to follow complex guidelines and self-audit work for consistency and accuracy
• Preferred: experience with data labeling tools, prompt evaluation, content safety labeling, or QA processes

Work Model

This is a full-time Remote role performed online with secure workflows. Open to candidates in the US, including Phoenix-based applicants.