AI Trainer — Data Annotation & Model Evaluation (ScaleAI Contractor, Remote)
Annotated and evaluated 12,000+ AI-generated responses to support RLHF training pipelines for LLM behavior refinement. Built high-quality prompts and adversarial test cases, then reviewed outputs for safety and factual accuracy failure modes. Worked with quality leads to maintain annotation consistency and documented policy-violating responses for alignment improvement cycles. • LLM response annotation across text summarization, Q&A, and code generation tasks • Adversarial testing to identify safety and factuality issues • Quality assurance focused on inter-rater agreement (consistently above 92%) • Policy-violation flagging and documentation for model alignment