Note: The job is a remote job and is open to candidates in USA. Rex.zone is seeking individuals to produce high-quality training data for machine learning and LLM systems. The role involves labeling and evaluating text and multimodal content, following strict annotation guidelines, and supporting workflows to improve model performance and content safety.
Responsibilities
- Execute text and prompt evaluation tasks, including LLM response grading
- Perform RLHF preference ranking and write clear rationales
- Conduct QA evaluation checks and dataset audits to improve training data quality
- Apply named entity recognition (NER) and taxonomy-driven labeling
- Support computer vision annotation (e.g., bounding boxes, polygons, segmentation) when required
- Perform content safety labeling and policy-based classification
- Participate in calibration sessions to reduce inter-annotator disagreement
Skills
- Hands-on experience with data annotation or evaluation for ML/LLM systems
- Strong attention to detail and consistent decision-making
- Comfort working with ambiguity and documenting edge cases
- Familiarity with RLHF, LLM evaluation, content safety labeling, and QA concepts
- Ability to work remotely with reliable connectivity and maintain confidentiality
- Experience with annotation tools, audits, and disagreement resolution workflows
- Exposure to computer vision annotation and spreadsheet-based QA
- Bilingual English/French helpful for Canada-focused datasets
Company Overview
- RemoExperts is a global platform where skilled professionals and tutors contribute to AI training across video, image, audio, text, code, math, and more. It was founded in 2025, and is headquartered in Palo Alto, California, US, with a workforce of 201-500 employees. Its website is https://www.remoexperts.com.