Isreal Odetunde

Key Skills

Software

Appen

Clickworker

OneForma

Toloka

Telus

CVAT

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Text

Video

Top Task Types

Text Summarization

Translation Localization

Freelancer Overview

I have hands-on experience supporting AI training data projects through annotation, labeling, and transcription tasks, where I worked with both image and text datasets. My responsibilities included accurately tagging data according to detailed guidelines, ensuring consistency across large volumes of files, and flagging irregularities to improve model training accuracy. With strong attention to detail and a fast typing speed (200+ WPM), I consistently delivered high-quality annotations under strict deadlines. In addition, I have contributed to content digitization and data entry projects, where I transcribed, formatted, and verified sensitive information while maintaining confidentiality. This background has equipped me with the ability to quickly learn new labeling tools, apply traffic rules and domain-specific knowledge, and work effectively in remote, fast-paced environments. My adaptability, technical proficiency, and commitment to accuracy make me well-suited for AI training data and annotation roles.

Labeling Experience

Traffic Sign & Road Object Annotation for Autonomous Vehicles

CVATVideoBounding BoxPolygon

Contributed to an AI training project focused on improving autonomous driving systems. Annotated large datasets of road scenes, including traffic signs, lane markings, pedestrians, and vehicles, using bounding boxes and polygon segmentation. Performed both image and short video sequence labeling to identify objects, classify traffic scenarios, and track object movement across frames. Ensured high-quality annotations by adhering to strict project guidelines and maintaining over 95% accuracy in audit reviews. Collaborated with a remote team and delivered annotations within tight deadlines to support timely model training.

Contributed to an AI training project focused on improving autonomous driving systems. Annotated large datasets of road scenes, including traffic signs, lane markings, pedestrians, and vehicles, using bounding boxes and polygon segmentation. Performed both image and short video sequence labeling to identify objects, classify traffic scenarios, and track object movement across frames. Ensured high-quality annotations by adhering to strict project guidelines and maintaining over 95% accuracy in audit reviews. Collaborated with a remote team and delivered annotations within tight deadlines to support timely model training.

2024 - 2024

Education

Work History