Happiness Audu

Key Skills

Software

Appen

Top Subject Matter

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Top Data Types

Text

Top Label Types

Data Collection

Audio Recording

Transcription

Freelancer Overview

I am an experienced AI Prompt Engineer and Annotation Specialist with over three years dedicated to enhancing AI and LLM performance through high-quality data labeling, annotation, and prompt engineering. My expertise spans NLP, computer vision, and audio data, where I have labeled and reviewed tens of thousands of samples for tasks such as summarization, classification, sentiment analysis, and extraction. I am proficient with leading annotation platforms like Labelbox, SuperAnnotate, and CVAT, as well as AI tools including ChatGPT, Claude, and Jasper. My work has directly contributed to reducing model hallucinations, improving dataset quality, and streamlining annotation workflows through reusable templates and structured feedback. I am passionate about ethical, user-aligned AI and thrive in collaborative, cross-functional environments where data quality and responsible AI are top priorities.

Labeling Experience

AI Text & Image Annotation Specialist

AppenTextData CollectionAudio Recording

Worked on large-scale AI training projects, labeling and annotating over 30,000 text, image, and audio samples. Tasks included text categorization, sentiment analysis, question answering, NER tagging, and object detection for computer vision datasets. Ensured data quality by following strict annotation guidelines, reviewing outputs for consistency, and flagging biased or hallucinated AI responses. Participated in prompt tuning for LLMs and AI output evaluation, improving dataset reliability and model performance. Collaborated with cross-functional teams to streamline workflows and optimize annotation processes.

Worked on large-scale AI training projects, labeling and annotating over 30,000 text, image, and audio samples. Tasks included text categorization, sentiment analysis, question answering, NER tagging, and object detection for computer vision datasets. Ensured data quality by following strict annotation guidelines, reviewing outputs for consistency, and flagging biased or hallucinated AI responses. Participated in prompt tuning for LLMs and AI output evaluation, improving dataset reliability and model performance. Collaborated with cross-functional teams to streamline workflows and optimize annotation processes.

2023 - 2025

Education

Work History