Ademuwagun Abdulrahman

Key Skills

Software

Labelbox

Scale AI

Remotasks

Top Subject Matter

Computer Vision

Natural Language Processing

Engineering Civil & Structural Infrastructure

Top Data Types

Image

Text

Top Task Types

Object Detection

RLHF

Segmentation

Freelancer Overview

AI Data Trainer & Annotation Specialist. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox, Scale AI, and Remotasks. Education includes Ordinary National Diploma, Rufus Giwa Polytechnic, Owo. AI-training focus includes data types such as Image and Text and labeling workflows including Object Detection, RLHF, and Segmentation.

Labeling Experience

AI Data Trainer & Annotation Specialist

RemotasksImageSegmentation

I segmented images for annotation purposes in support of computer vision systems. Tasks entailed identifying and outlining objects to support tasks such as semantic segmentation and classification. These efforts directly enhanced the training quality of vision-based AI models. • Utilized Remotasks, Labelbox, and Toloka for efficient data handling. • Collaborated remotely to update and refine segmentation protocols. • Managed multi-step labeling workflows using Notion. • Leveraged AI automation for preliminary image screening tasks.

I segmented images for annotation purposes in support of computer vision systems. Tasks entailed identifying and outlining objects to support tasks such as semantic segmentation and classification. These efforts directly enhanced the training quality of vision-based AI models. • Utilized Remotasks, Labelbox, and Toloka for efficient data handling. • Collaborated remotely to update and refine segmentation protocols. • Managed multi-step labeling workflows using Notion. • Leveraged AI automation for preliminary image screening tasks.

2022 - Present

AI Data Trainer & Annotation Specialist

Scale AITextRLHF

I performed Reinforcement Learning from Human Feedback (RLHF) tasks to improve Large Language Models (LLMs). Activities included ranking, fact-checking, and evaluating AI responses for safety, accuracy, and helpfulness. Strict adherence to project protocols ensured data quality and robust model training. • Consistently ranked outputs from multiple AI chatbots for comparative evaluation. • Conducted detailed sentiment analysis and entity recognition tasks. • Used Scale AI, Remotasks, and Toloka platforms for various NLP annotation projects. • Maintained project records and progress through Notion tracking tools.

I performed Reinforcement Learning from Human Feedback (RLHF) tasks to improve Large Language Models (LLMs). Activities included ranking, fact-checking, and evaluating AI responses for safety, accuracy, and helpfulness. Strict adherence to project protocols ensured data quality and robust model training. • Consistently ranked outputs from multiple AI chatbots for comparative evaluation. • Conducted detailed sentiment analysis and entity recognition tasks. • Used Scale AI, Remotasks, and Toloka platforms for various NLP annotation projects. • Maintained project records and progress through Notion tracking tools.

2022 - Present

AI Data Trainer & Annotation Specialist

LabelboxImageObject Detection

As an AI Data Trainer & Annotation Specialist, I annotated large image datasets for computer vision models, focusing on object detection and categorization. My work ensured a 98%+ accuracy rate through detailed application of bounding boxes and semantic segmentation. Collaboration with research teams improved project guidelines and handled complex edge cases effectively. • Maintained precise bounding box and segmentation labels per project specifications. • Adapted to evolving edge-case scenarios by updating annotation guidelines. • Employed Labelbox, Scale AI, and Remotasks for efficient image data management. • Leveraged Notion and AI automation to increase workflow throughput without sacrificing quality.

As an AI Data Trainer & Annotation Specialist, I annotated large image datasets for computer vision models, focusing on object detection and categorization. My work ensured a 98%+ accuracy rate through detailed application of bounding boxes and semantic segmentation. Collaboration with research teams improved project guidelines and handled complex edge cases effectively. • Maintained precise bounding box and segmentation labels per project specifications. • Adapted to evolving edge-case scenarios by updating annotation guidelines. • Employed Labelbox, Scale AI, and Remotasks for efficient image data management. • Leveraged Notion and AI automation to increase workflow throughput without sacrificing quality.

2022 - Present

Education

Work History