Overview Rex.zone is recruiting for high-demand STEM roles aligned to AI/ML training workflows and applied engineering. These are remote, full-time opportunities supporting large language model evaluation, RLHF-adjacent feedback loops, data labeling, QA evaluation, prompt evaluation, and training data quality across NLP, computer vision, and content safety. What You Will Do
Produce and/or validate high-quality labels, judgments, and evaluations for AI systems
Follow and improve annotation guidelines compliance; document edge cases and rubric updates
Run QA sampling, adjudication workflows, and inter-annotator agreement calibration
Perform error analysis and structured evaluation to drive model performance improvement
Support LLM training pipelines with prompt evaluation and safety/reliability assessments
Example focus areas (role-dependent)
NLP: named entity recognition, text classification, intent labeling
Content safety labeling and policy-aligned evaluation
Data/ML engineering: data pipelines, evaluation harnesses, monitoring and drift checks
How To Apply Apply on Rex.zone and confirm eligibility during the application process. Align your resume to skills like QA evaluation, data labeling, prompt evaluation, and training data quality.