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Rex.zone is seeking a Remote Data Annotator to label and evaluate datasets used to train ML models. You will contribute to RLHF feedback loops and ensure data quality across NLP, CV, and LLM workflows.
The role emphasizes high-precision labeling, adherence to guidelines, and collaboration with QA, reviewers, and data operations teams from a remote setup in New York.
As a Remote Data Annotator supporting New York-based programs, you will label and evaluate datasets used to train and validate machine learning models. Your work improves training data quality, supports RLHF feedback loops, and drives model performance improvement across NLP, computer vision, and LLM workflows.
These roles are Remote and can be performed from New York. Some projects may require availability aligned with US business hours or structured QA review cycles.