Fadhlullah Mustapha

Key Skills

Software

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Text Generation

Computer Programming Coding

Data Collection

Freelancer Overview

I have experience supporting AI training processes through data review, categorization, and quality checking tasks that improve model accuracy and consistency. I am skilled at following annotation guidelines, identifying patterns in text or data, and ensuring labeled datasets remain clear, structured, and reliable for machine learning applications. My strengths include strong attention to detail, analytical thinking, and the ability to work efficiently while maintaining accuracy. I am comfortable handling repetitive tasks, meeting deadlines, and maintaining data confidentiality, which allows me to contribute effectively to data labeling and AI training workflows.

Labeling Experience

AI Conversational Data Annotation for Chatbot Training

AppenTextText GenerationComputer Programming Coding

Worked on annotating and organizing conversational text data to support AI chatbot training and evaluation. Tasks included classifying user intents, labeling named entities, reviewing prompt-response pairs, and rating model outputs for relevance, accuracy, and safety. Maintained consistency by following structured annotation guidelines and performing quality checks to ensure high data reliability. The project involved handling diverse conversational datasets, improving response quality through feedback annotations, and ensuring data confidentiality standards were maintained. Emphasis was placed on accuracy, consistency, and adherence to labeling instructions to optimize training data for supervised fine-tuning and model evaluation.

Worked on annotating and organizing conversational text data to support AI chatbot training and evaluation. Tasks included classifying user intents, labeling named entities, reviewing prompt-response pairs, and rating model outputs for relevance, accuracy, and safety. Maintained consistency by following structured annotation guidelines and performing quality checks to ensure high data reliability. The project involved handling diverse conversational datasets, improving response quality through feedback annotations, and ensuring data confidentiality standards were maintained. Emphasis was placed on accuracy, consistency, and adherence to labeling instructions to optimize training data for supervised fine-tuning and model evaluation.

2025 - 2025

Education

Work History