Margaret Sisia

Key Skills

Software

CloudFactory

Top Subject Matter

No subject matter listed

Top Data Types

Video

Top Task Types

Bounding Box

Segmentation

Freelancer Overview

I am a detail-oriented data specialist with over five years of hands-on experience in data annotation, quality assurance, and AI training across diverse domains including computer vision, NLP, and audio data. My background includes leading and mentoring remote annotation teams, designing annotation guidelines, and collaborating closely with machine learning engineers to improve model accuracy. I am skilled in labeling images, video, audio, and text using common annotation platforms, and have a proven track record of optimizing labeling workflows, implementing QA processes, and driving continuous improvement through data analysis. I am comfortable managing large-scale projects, training annotators, and supporting human-in-the-loop AI model development, and bring strong communication and technical documentation skills to every project.

Labeling Experience

Data Labelling

CloudfactoryVideoBounding BoxSegmentation

Worked on AI data labelling projects at CloudFactory, focusing on preparing high-quality datasets for training machine learning and large language models. The project involved annotating and reviewing audio, text, and image data, with a strong emphasis on audio labelling for speech recognition, transcription, speaker identification, and audio classification. Responsibilities included applying clear labelling guidelines, training and supporting annotators, monitoring quality and consistency, and improving datasets based on error analysis. The work ensured accurate, reliable data and contributed to models that were ready for deployment and real-world use.

Worked on AI data labelling projects at CloudFactory, focusing on preparing high-quality datasets for training machine learning and large language models. The project involved annotating and reviewing audio, text, and image data, with a strong emphasis on audio labelling for speech recognition, transcription, speaker identification, and audio classification. Responsibilities included applying clear labelling guidelines, training and supporting annotators, monitoring quality and consistency, and improving datasets based on error analysis. The work ensured accurate, reliable data and contributed to models that were ready for deployment and real-world use.

2023 - 2025

Education

Work History