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Segun Akanbi

Segun Akanbi

AI Data & Backend Engineer (Audio, Image & Code Annotation)

Nigeria flagLagos, Nigeria
$12.00/hrEntry LevelInternal Proprietary ToolingOtherLabel Studio

Key Skills

Software

Internal/Proprietary Tooling
Other
Label StudioLabel Studio

Top Subject Matter

Artificial Intelligence & Machine Learning (Training Data, NLP, Computer Vision)
Financial Technology (Payments, Fraud Detection, Identity Verification)
Logistics & Mobility (Delivery Systems, Tracking, Route Optimisation)

Top Data Types

Computer Code ProgrammingComputer Code Programming
ImageImage
AudioAudio

Top Task Types

TranscriptionTranscription
ClassificationClassification
Computer Programming/CodingComputer Programming/Coding

Freelancer Overview

Backend Engineer. Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Experienced with large-scale dataset handling and annotation consistency standards and familiar with AI data pipeline concepts, including preprocessing, labeling, and validation.

Entry LevelEnglishYoruba

Labeling Experience

AI Image Classification & Data Annotation Specialist

ImageClassification
Contributed to large-scale computer vision datasets by performing image classification and annotation tasks for AI model training. Labeled and categorized images based on predefined taxonomies, ensuring accurate classification across multiple categories and edge cases. Applied strict annotation guidelines to maintain consistency, including handling ambiguous images, low-quality inputs, and multi-label scenarios. Participated in quality assurance processes such as validation, re-labeling, and cross-review to ensure high dataset accuracy and reliability. Supported the development of machine learning models by delivering clean, structured, and high-quality labeled image data.

Contributed to large-scale computer vision datasets by performing image classification and annotation tasks for AI model training. Labeled and categorized images based on predefined taxonomies, ensuring accurate classification across multiple categories and edge cases. Applied strict annotation guidelines to maintain consistency, including handling ambiguous images, low-quality inputs, and multi-label scenarios. Participated in quality assurance processes such as validation, re-labeling, and cross-review to ensure high dataset accuracy and reliability. Supported the development of machine learning models by delivering clean, structured, and high-quality labeled image data.

2025 - 2026

AI Audio Transcription & Data Annotation Specialist (Outlier AI)

AudioTranscription
Worked on large-scale AI training datasets performing high-quality audio transcription and annotation tasks for speech recognition and natural language processing models. Transcribed diverse audio inputs including conversations, interviews, and task-based recordings while maintaining strict accuracy and formatting guidelines. Applied detailed annotation standards such as speaker identification, punctuation normalization, timestamp alignment, and noise handling to ensure high-quality labeled data. Participated in quality assurance workflows, including review cycles, error correction, and adherence to consistency guidelines across datasets. Contributed to improving model performance by ensuring clean, structured, and reliable training data for machine learning pipelines.

Worked on large-scale AI training datasets performing high-quality audio transcription and annotation tasks for speech recognition and natural language processing models. Transcribed diverse audio inputs including conversations, interviews, and task-based recordings while maintaining strict accuracy and formatting guidelines. Applied detailed annotation standards such as speaker identification, punctuation normalization, timestamp alignment, and noise handling to ensure high-quality labeled data. Participated in quality assurance workflows, including review cycles, error correction, and adherence to consistency guidelines across datasets. Contributed to improving model performance by ensuring clean, structured, and reliable training data for machine learning pipelines.

2025 - 2026

Education

U

University of Michigan

Building Web Applications in PHP, Computer Science

Building Web Applications in PHP
2019 - 2019
J

John Hopkins University

HTML, CSS, and Javascript for Web Developers, Computer Science

HTML, CSS, and Javascript for Web Developers
2017 - 2018

Work History

F

Freelance

Backend Engineer

Lagos
2023 - Present
T

Tramango

Lead Backend Engineer

Lagos
2022 - 2023