STEM Jobs in India
Rex.zone · United States
- On site
- Full-time
- United States
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About the role
STEM Jobs in India (Remote, Full-Time)
Rex.zone connects candidates to engineering and applied AI/ML workflows that power large language model training pipelines. You will support training data quality through data labeling, RLHF evaluation, QA evaluation, and guideline-based reviews across NLP, computer vision, and content safety domains.
What You Will Do
Web-based annotation tools, spreadsheet QA workflows, issue tracking, versioned guidelines, and structured rubrics.
Work is designed for distributed collaboration.
Rex.zone connects candidates to engineering and applied AI/ML workflows that power large language model training pipelines. You will support training data quality through data labeling, RLHF evaluation, QA evaluation, and guideline-based reviews across NLP, computer vision, and content safety domains.
What You Will Do
- Execute data labeling for NLP and computer vision using clear taxonomies and instructions
- Perform RLHF-style preference ranking and rubric-based scoring for LLM outputs
- Run QA evaluation for completeness, consistency, and annotation guidelines compliance
- Conduct prompt evaluation and error categorization to surface model failure modes
- Perform named entity recognition (NER) and span labeling with strict boundary rules
- Support content safety labeling (e.g., harassment, self-harm, regulated goods)
- Maintain audit trails, adjudication notes, and participate in calibration sessions
- Communicate findings to stakeholders to drive measurable model performance improvement
- STEM background or equivalent engineering experience
- High attention to detail; ability to follow detailed specifications and handle edge cases
- Experience with QA evaluation, data labeling, or structured review workflows
- Strong documentation skills and consistency at scale in a metrics-driven environment
- Experience with RLHF, LLM evaluation, prompt evaluation, or ranking tasks
- Familiarity with NER, text classification, or computer vision annotation
- Exposure to content safety labeling and policy categories
- Experience improving training data quality via audits and inter-annotator agreement
Web-based annotation tools, spreadsheet QA workflows, issue tracking, versioned guidelines, and structured rubrics.
Work is designed for distributed collaboration.