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Michelle

Michelle

AI Model Evaluator - Technology & Internet

Nigeria flagAbuja, Nigeria
$9.00/hrIntermediateAppen

Key Skills

Software

AppenAppen

Top Subject Matter

No subject matter listed

Top Data Types

AudioAudio
DocumentDocument
Geospatial Tiled ImageryGeospatial Tiled Imagery
ImageImage
VideoVideo

Top Task Types

Audio RecordingAudio Recording
Bounding BoxBounding Box
Entity (NER) ClassificationEntity (NER) Classification

Freelancer Overview

I am a detail-oriented AI evaluator and data annotator with hands-on experience in assessing AI-generated outputs for accuracy, bias, safety, and relevance. My background includes working on freelance projects and academic research, where I have evaluated thousands of large language model (LLM) responses using rubric-based scoring and contributed to NLP tasks such as sentiment analysis and entity recognition. I am skilled in Python, familiar with AI/ML tools like Hugging Face Transformers and TensorFlow, and have used bias detection frameworks to identify ethical issues in model outputs. My work has led to measurable improvements in model safety and quality, and I am passionate about contributing to ethical AI development by providing structured feedback and high-quality training data.

IntermediateIgboEnglish

Labeling Experience

Appen

Data Collection and Annotation

AppenVideoBounding BoxEntity Ner Classification
Contributed to large-scale data annotation projects supporting the development and evaluation of Large Language Models [LLMs] and computer vision systems. Performed precise bounding box annotations on dynamic video datasets, labelling objects and actions across multiple frames while maintaining temporal consistency. Additionally, I carried out text classification tasks by categorizing textual data on predefined labels such as intent, relevance, and content type to support LLM training and evaluation. I followed strict annotation guidelines, participated in quality control processes and consistently met accurate benchmarks to ensure high quality training data for AI model performance and scalability. I am full time Data Collector and very much an outfield worker.

Contributed to large-scale data annotation projects supporting the development and evaluation of Large Language Models [LLMs] and computer vision systems. Performed precise bounding box annotations on dynamic video datasets, labelling objects and actions across multiple frames while maintaining temporal consistency. Additionally, I carried out text classification tasks by categorizing textual data on predefined labels such as intent, relevance, and content type to support LLM training and evaluation. I followed strict annotation guidelines, participated in quality control processes and consistently met accurate benchmarks to ensure high quality training data for AI model performance and scalability. I am full time Data Collector and very much an outfield worker.

2023 - 2025

Education

U

University of Toronto

Bachelor of Science, Computer Science (Artificial Intelligence Specialization)

Bachelor of Science
2021 - 2025

Work History

U

University Of Toronto

AI Research Intern

Toronto
2024 - Present
U

University Of Toronto

Campus Tech Support Assistant

Toronto
2022 - 2024