About Rex.zone
Rex.zone builds AI-powered recruiting and talent solutions. This remote role focuses on building, evaluating, and deploying AI systems used in real-world ML training pipelines—LLM applications, RLHF workflows, data labeling automation, QA evaluation, prompt evaluation, and model performance improvement.
Responsibilities
- Build and maintain AI services for training and inference (batch + real-time APIs)
- Implement evaluation harnesses for LLM evaluation, prompt evaluation, and regression testing
- Integrate RLHF feedback loops and human review tooling to improve model behavior
- Develop data pipelines supporting data labeling, NER, and computer vision annotation at scale
- Define metrics for model performance improvement and monitor quality drift in production
- Partner with annotators/QA to enforce annotation guidelines compliance and resolve edge cases
- Contribute to content safety labeling workflows (policy routing, moderation, audits)
Preferred Background
- Strong Python engineering with ML frameworks (PyTorch/TensorFlow) and API development
- Experience with LLM pipelines, evaluation datasets, and prompt iteration
- Familiarity with MLOps, CI/CD, containerization, and cloud deployment
- Knowledge of NLP (NER, classification, retrieval) and/or CV (detection, segmentation)
How To Apply
Apply via Rex.zone and include examples of shipped ML systems, evaluation frameworks, and deployment/debugging work.
Compensation: $30–$50 per hour (base).