Adedamola Fasakin

Key Skills

Software

CVAT

Labelbox

Doccano

Top Subject Matter

No subject matter listed

Top Data Types

Video

Image

Audio

Top Label Types

Bounding Box

Action Recognition

Tracking

Polygon

Segmentation

Emotion Recognition

Object Detection

Audio Recording

Transcription

Freelancer Overview

I am a detail-oriented Data Annotation Specialist with over 2 years of hands-on experience preparing and quality-checking datasets for machine learning and AI model training. My work spans text, image, audio, and video annotation for projects in natural language processing, computer vision, and speech recognition, supporting domains such as e-commerce, healthcare, autonomous vehicles, and content moderation. I consistently deliver high-accuracy results—maintaining a 98%+ accuracy rate—by following rigorous guidelines and collaborating closely with AI researchers and engineers to refine annotation protocols and resolve edge cases. I am highly skilled in using platforms like Labelbox, Scale AI, and Amazon SageMaker Ground Truth, and have completed over 30 projects, adapting quickly to new requirements and maintaining strict confidentiality standards. My analytical mindset, attention to detail, and proactive communication ensure that I contribute positively to both the quality and efficiency of AI training data workflows.

Labeling Experience

Audio Annotator/ Dataset Manager

DoccanoAudioEmotion RecognitionAudio Recording

Contributed to a comprehensive audio annotation initiative focused on developing high-quality training datasets for multimodal large language models (LLMs) with audio understanding capabilities. Performed detailed transcription, classification, and segmentation of diverse audio content including speech, environmental sounds, music, and multi-speaker conversations to enable AI models to process, understand, and generate insights from acoustic information.

Contributed to a comprehensive audio annotation initiative focused on developing high-quality training datasets for multimodal large language models (LLMs) with audio understanding capabilities. Performed detailed transcription, classification, and segmentation of diverse audio content including speech, environmental sounds, music, and multi-speaker conversations to enable AI models to process, understand, and generate insights from acoustic information.

2025 - 2025

Image labeller

LabelboxImageBounding BoxPolygon

Executed large-scale image annotation project to develop high-quality training datasets for multimodal large language models (LLMs) with visual understanding capabilities. Leveraged Computer Vision Annotation Tool (CVAT& Labelbox) to perform precise labeling of diverse image content, enabling AI models to recognize objects, understand spatial relationships, interpret visual context, and generate accurate descriptions of visual scenes.

Executed large-scale image annotation project to develop high-quality training datasets for multimodal large language models (LLMs) with visual understanding capabilities. Leveraged Computer Vision Annotation Tool (CVAT& Labelbox) to perform precise labeling of diverse image content, enabling AI models to recognize objects, understand spatial relationships, interpret visual context, and generate accurate descriptions of visual scenes.

2025 - 2025

Video Labeller/Annotator

CVATVideoBounding BoxAction Recognition

Collaborated on a comprehensive video annotation project designed to generate high-quality training datasets for multimodal large language models (LLMs). Utilized Computer Vision Annotation Tool (CVAT) to perform frame-by-frame labeling of video content, enabling AI models to understand visual context, temporal relationships, and semantic meaning across diverse video scenarios.

Collaborated on a comprehensive video annotation project designed to generate high-quality training datasets for multimodal large language models (LLMs). Utilized Computer Vision Annotation Tool (CVAT) to perform frame-by-frame labeling of video content, enabling AI models to understand visual context, temporal relationships, and semantic meaning across diverse video scenarios.

2025 - 2025

Education

Work History