Ian Njogu

Key Skills

Software

Labelbox

CVAT

Top Subject Matter

Age group classification

visual appearance

Demographics Domain Expertise

Top Data Types

Image

Audio

Text

Document

Top Label Types

Classification

Transcription

Freelancer Overview

Freelance AI Image Review Specialist. Brings 2+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Labelbox, CVAT, and Otter.ai. Education includes Bachelor of Science, Jomo Kenyatta University of Agriculture and Technology and Certificate, Macclesfield College. AI-training focus includes data types such as Image and Audio and labeling workflows including Classification and Transcription.

Labeling Experience

Freelance Transcription Specialist

AudioTranscription

As a Freelance Transcription Specialist, I transcribed various audio recordings into accurate written text for speech recognition datasets. This included speaker identification and timestamping using reliable software tools. My work helped establish high transcription accuracy for diverse sources. • Converted audio to text for dataset creation • Identified speakers and added timestamps to transcripts • Reviewed text for grammar and contextual precision • Enhanced AI speech model training data with human-verified outputs

As a Freelance Transcription Specialist, I transcribed various audio recordings into accurate written text for speech recognition datasets. This included speaker identification and timestamping using reliable software tools. My work helped establish high transcription accuracy for diverse sources. • Converted audio to text for dataset creation • Identified speakers and added timestamps to transcripts • Reviewed text for grammar and contextual precision • Enhanced AI speech model training data with human-verified outputs

Present

Freelance AI Image Review Specialist

LabelboxImageClassification

As a Freelance AI Image Review Specialist, I reviewed and classified thousands of images to support age-related AI learning tasks. My main focus was to assign accurate age-group labels based on strict annotation guidelines. I consistently maintained dataset quality and flagged problematic images for further review. • Applied detailed image review processes for AI model preparation • Ensured label consistency and guideline compliance • Identified and flagged ambiguous or low-quality data • Supported AI model improvement through human-reviewed datasets

As a Freelance AI Image Review Specialist, I reviewed and classified thousands of images to support age-related AI learning tasks. My main focus was to assign accurate age-group labels based on strict annotation guidelines. I consistently maintained dataset quality and flagged problematic images for further review. • Applied detailed image review processes for AI model preparation • Ensured label consistency and guideline compliance • Identified and flagged ambiguous or low-quality data • Supported AI model improvement through human-reviewed datasets

2025 - 2026

AI Data Annotator (Image & Text)

CVATImageClassification

As an AI Data Annotator, I labeled large-scale image datasets with visual and demographic classes for AI development. I followed strict annotation rules to minimize bias and error. I participated in dataset quality audits, consistently maintaining high accuracy. • Labeled and classified image data based on project needs • Applied bias minimization practices • Supported quality assurance and audit cycles • Focused on consistent accuracy and reliable annotations

As an AI Data Annotator, I labeled large-scale image datasets with visual and demographic classes for AI development. I followed strict annotation rules to minimize bias and error. I participated in dataset quality audits, consistently maintaining high accuracy. • Labeled and classified image data based on project needs • Applied bias minimization practices • Supported quality assurance and audit cycles • Focused on consistent accuracy and reliable annotations

2023 - 2024

Transcription Contributor (Portfolio Project)

AudioTranscription

As a Transcription Contributor for the Audio Transcription Dataset project, I converted audio samples into accurate, timestamped text for AI speech training. Tasks included speaker labeling and detailed formatting to match dataset standards. Results enhanced the quality and usability of speech recognition resources. • Transcribed and formatted audio for AI use • Labeled speakers and inserted timestamp data • Improved dataset organization and accessibility • Enhanced output transcription quality for AI training

As a Transcription Contributor for the Audio Transcription Dataset project, I converted audio samples into accurate, timestamped text for AI speech training. Tasks included speaker labeling and detailed formatting to match dataset standards. Results enhanced the quality and usability of speech recognition resources. • Transcribed and formatted audio for AI use • Labeled speakers and inserted timestamp data • Improved dataset organization and accessibility • Enhanced output transcription quality for AI training

Not specified

Annotation Reviewer (Portfolio Project)

LabelboxImageClassification

In the Bias & Fairness Review project, I reviewed annotated datasets to ensure labeling accuracy without introducing demographic or subjective bias. My evaluation helped maintain fairness and prevent inappropriate assumptions in data-driven classifications. My work supported responsible AI model development. • Conducted annotation reviews for fairness • Avoided unsupported or sensitive assumptions in data • Reinforced ethical, unbiased labeling processes • Aided trustworthy AI performance through reviews

In the Bias & Fairness Review project, I reviewed annotated datasets to ensure labeling accuracy without introducing demographic or subjective bias. My evaluation helped maintain fairness and prevent inappropriate assumptions in data-driven classifications. My work supported responsible AI model development. • Conducted annotation reviews for fairness • Avoided unsupported or sensitive assumptions in data • Reinforced ethical, unbiased labeling processes • Aided trustworthy AI performance through reviews

Not specified

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Education

Work History