What are the responsibilities and job description for the Remote Data Labeling Jobs in Phoenix position at Rex.zone?
Remote Data Labeling Specialist (Phoenix)
Remote data labeling jobs in Phoenix are mid-senior, full-time roles focused on creating and validating training data for AI systems. You will label text, images, video, and audio; follow annotation guidelines compliance; run QA evaluation; and support RLHF and prompt evaluation to improve large language model evaluation and model performance improvement.
About The Role
You will produce high-quality labeled datasets that power AI/ML model training and evaluation. Day-to-day work includes labeling and reviewing tasks across NLP and computer vision, applying consistent taxonomy and edge-case handling, and documenting decisions to maintain training data quality.
What You Will Do
This is a Remote, FULL_TIME role aligned to Phoenix candidates and time zones as needed. You will collaborate asynchronously with data operations, QA reviewers, and engineering stakeholders using web-based annotation tools, RLHF rubrics, and QA dashboards.
Pay
Competitive hourly pay: $30–$50 per hour (USD).
Remote data labeling jobs in Phoenix are mid-senior, full-time roles focused on creating and validating training data for AI systems. You will label text, images, video, and audio; follow annotation guidelines compliance; run QA evaluation; and support RLHF and prompt evaluation to improve large language model evaluation and model performance improvement.
About The Role
You will produce high-quality labeled datasets that power AI/ML model training and evaluation. Day-to-day work includes labeling and reviewing tasks across NLP and computer vision, applying consistent taxonomy and edge-case handling, and documenting decisions to maintain training data quality.
What You Will Do
- Execute data labeling for text, image, video, and audio; apply annotation guidelines and flag ambiguous cases
- Perform named entity recognition, sentiment/intent tagging, and instruction-following judgments for LLM training pipelines
- Support RLHF by ranking model responses, rubric-based scoring, and prompt evaluation
- Conduct QA evaluation (spot checks, inter-annotator agreement checks, error categorization, rework coordination, final dataset sign-off)
- Audit outputs for content safety labeling and policy-driven requirements
- Mid-senior experience in data labeling/data annotation programs with measurable quality outcomes
- Strong guideline interpretation, consistency, and clear adjudication notes for edge cases
- Familiarity with QA evaluation concepts (inter-annotator agreement, error taxonomies)
- Working knowledge of NLP and computer vision annotation (e.g., NER, bounding boxes/polygons)
This is a Remote, FULL_TIME role aligned to Phoenix candidates and time zones as needed. You will collaborate asynchronously with data operations, QA reviewers, and engineering stakeholders using web-based annotation tools, RLHF rubrics, and QA dashboards.
Pay
Competitive hourly pay: $30–$50 per hour (USD).
Salary : $30 - $50