Applied Scientist
Led the development and implementation of large-scale tool integration systems, achieving significant improvements in tool invocation accuracy and system performance:• Spearheaded the successful onboarding of 1000+ tools using the converse method, implementing structured JSON formatting and Amazon-specific dataset creation with 76 tools and 300 test conversations• Drove substantial performance improvements, elevating accuracy from 45% (baseline) to 85% through innovative solutions including enhanced tool parameter handling and top-k tool selection methodology• Architected and implemented key technical solutions including embedding-based tool selection, conversation memory management, and robust validation mechanisms• Developed comprehensive testing infrastructure and documentation, enabling systematic performance evaluation and future scalability• Demonstrated expertise in large language models, tool integration, and conversation AI systems while maintaining high standards of code quality and system reliability
