Ifeoluwa Oladeinde

Key Skills

Software

CVAT

Labelbox

Remotasks

Scale AI

Appen

Top Subject Matter

AI training data for automotive

Medical Domain Expertise

and traffic datasets

Top Data Types

Image

Text

Document

Top Task Types

Bounding Box

Classification

Freelancer Overview

Freelance Image Annotation Specialist. Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include CVAT, Labelbox, and Remotasks. Education includes Bachelor of Engineering, Federal University of Technology Akure (2023). AI-training focus includes data types such as Image and labeling workflows including Bounding Box and Classification.

Labeling Experience

Freelance Image Annotation Specialist

CVATImageBounding Box

As an Image Annotation Specialist with Remotasks and Scale AI, I annotated high volumes of images for object detection, semantic segmentation, and classification tasks. I drew bounding boxes, polygons, and keypoints for various subjects including pedestrians, vehicles, and medical imagery. I used tools such as CVAT, Labelbox, and Remotasks’ proprietary platform to ensure over 95% annotation accuracy. • Delivered 500–1,000 annotated images per day, consistently meeting project deadlines. • Reviewed and validated team annotations for quality assurance. • Maintained rework rates below 3% while handling time-sensitive batches. • Labeled more than 50,000 images spanning multiple domains and categories.

As an Image Annotation Specialist with Remotasks and Scale AI, I annotated high volumes of images for object detection, semantic segmentation, and classification tasks. I drew bounding boxes, polygons, and keypoints for various subjects including pedestrians, vehicles, and medical imagery. I used tools such as CVAT, Labelbox, and Remotasks’ proprietary platform to ensure over 95% annotation accuracy. • Delivered 500–1,000 annotated images per day, consistently meeting project deadlines. • Reviewed and validated team annotations for quality assurance. • Maintained rework rates below 3% while handling time-sensitive batches. • Labeled more than 50,000 images spanning multiple domains and categories.

2023 - Present

Data Collection & Labeling Assistant

AppenImageClassification

As a Data Collection & Labeling Assistant at Appen, I participated in large-scale AI data projects involving image categorization and scene description. I was responsible for labeling datasets designed for autonomous driving, retail product identification, and natural language image captioning. My work required following strict annotation guidelines to ensure quality and consistency for AI model development. • Labeled images for projects in autonomous vehicles and retail environments. • Provided visual recognition labeling and scene categorization. • Ensured adherence to client annotation standards and style guides. • Communicated regularly with project managers for clarification and accuracy.

As a Data Collection & Labeling Assistant at Appen, I participated in large-scale AI data projects involving image categorization and scene description. I was responsible for labeling datasets designed for autonomous driving, retail product identification, and natural language image captioning. My work required following strict annotation guidelines to ensure quality and consistency for AI model development. • Labeled images for projects in autonomous vehicles and retail environments. • Provided visual recognition labeling and scene categorization. • Ensured adherence to client annotation standards and style guides. • Communicated regularly with project managers for clarification and accuracy.

2022 - 2023

Education

Work History