FRANKLYN MWOGI

I am a detail-oriented Data Annotator and AI Training Specialist with hands-on experience labelling, validating, and quality-checking large datasets for machine learning and AI systems. I work across text, image, audio, and video modalities and follow strict guidelines to ensure high dataset consistency and accuracy.

As a freelance Data Annotator and AI Trainer I annotated and reviewed large volumes of data, applied labelling guidelines, and performed quality checks to identify and correct annotation errors. I regularly met productivity targets while maintaining precision and collaborated with reviewers and project managers to resolve discrepancies.

My project work includes large-scale text classification for sentiment and topic tagging that improved model training accuracy, and image annotation with bounding boxes and segmentation masks meeting pixel-level requirements for object detection. I am familiar with tools such as Labelbox, Amazon SageMaker Ground Truth, Appen/Remotasks/Scale AI platforms, and spreadsheet tools for dataset management.

I prioritize data quality, confidentiality, and compliance with AI ethics and data privacy standards. I am comfortable working independently or in teams, handling repetitive tasks and tight deadlines, and bringing consistent attention to detail and strong written English comprehension to every project.