Computer Representative Management
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Function CallingI worked on a text-based data labeling initiative centered around customer representative management scenarios. My responsibilities included annotating customer service conversations, labeling intent categories, and tagging function-calling sequences designed to train AI models on how to effectively handle real-world customer interactions. Each task required careful attention to detail to ensure that the labeled data accurately reflected the nuances of various customer communication styles and service situations, contributing meaningfully to the development of intelligent, responsive AI systems. In addition to the annotation work, I reviewed and categorized text data spanning multiple customer query types, including complaints, general inquiries, and escalation cases. Throughout the entire process, I maintained a high level of accuracy and consistency, strictly adhering to the project-specific quality guidelines provided. My commitment to precision ensured that the dataset met the standards required for effective model training, ultimately supporting the creation of AI solutions capable of navigating complex and sensitive customer service environments with confidence and reliability.
Prompt + Response Writing (SFT)