Multi-Turn LLM Evaluation & RLHF Alignment Pipeline
Scope & Objectives: Orchestrated a high-precision data annotation initiative focused on fine-tuning and aligning frontier Large Language Models (LLMs) via RLHF and multi-turn prompt evaluation. Tasks Performed: Managed the end-to-end data pipeline including complex prompt-response ranking, truthfulness verification, hallucination detection, and semantic safety filtering. Quality Measures & Delivery: Maintained a strict 97%+ consensus score across all annotators through multi-layered Quality Assurance (QA) reviews and real time feedback loops. All datasets were processed following clean data lineage standards and baseline security controls aligned with ISO 27001 data privacy practices to ensure zero leakage