Navigate AI - AI Product Manager

• Own model evaluation and quality standards. • Take full ownership of all evaluation systems, validation sets, and quality metrics. • Establish and maintain “golden sets” for every product as the source of truth for quality and accuracy. • Drive measurable accuracy improvements across products by leading initiatives to improve precision, recall, and overall model performance. • Define and track AI performance metrics and client SLAs while scaling operations. • Automate workflows that were previously manual QA or data entry processes through redesigning them for automation purposes. • Reduce human intervention by increasing the confidence of models to enhance reliability and repeatability in their outputs. • Build scalable evaluation pipelines capable of quickly evaluating pilots and active customers, ensuring high accuracy metrics even as customer volume grows. • Close the real-world feedback loop by capturing model errors from actual use cases, prioritizing them for continuous improvement with Engineering teams.