Opeyemi Akinade

Key Skills

Software

Label Studio

Appen

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Audio

Document

Image

Text

Video

Top Label Types

Data Collection

Emotion Recognition

Evaluation Rating

Prompt Response Writing SFT

Text Summarization

Transcription

Translation Localization

Freelancer Overview

I am a detail-oriented data labeling and AI training contributor with hands-on experience in annotating text, image, and video datasets to enhance machine learning model performance. My background includes evaluating AI-generated responses for empathy, relevance, clarity, and safety, as well as ensuring strict compliance with project guidelines and quality standards. I have worked extensively with annotation tools such as Label Studio, CVAT, and proprietary platforms, and am skilled in both natural language processing tasks and computer vision projects like egocentric video annotation. My strengths include a keen eye for error detection, strong written communication, and the ability to maintain high accuracy under tight deadlines while adapting quickly to new systems and complex annotation requirements.

Labeling Experience

AI Data Annotator / AI Training Contributor

Label StudioTextEvaluation Rating

Reviewed and evaluated AI-generated text responses based on structured criteria and project guidelines. Selected higher-quality responses with written justifications and identified inconsistencies in output. Maintained high accuracy while suggesting improvements to labeling processes. • Applied empathy, relevance, clarity, and safety guidelines to ratings • Compared multiple AI outputs and flagged ambiguous cases • Contributed to ongoing enhancement of annotation guidelines • Achieved productivity targets while preserving accuracy

Reviewed and evaluated AI-generated text responses based on structured criteria and project guidelines. Selected higher-quality responses with written justifications and identified inconsistencies in output. Maintained high accuracy while suggesting improvements to labeling processes. • Applied empathy, relevance, clarity, and safety guidelines to ratings • Compared multiple AI outputs and flagged ambiguous cases • Contributed to ongoing enhancement of annotation guidelines • Achieved productivity targets while preserving accuracy

2024

Audio Data Labeling Specialist

AppenAudioText GenerationAction Recognition

Labeled and categorized audio datasets for machine learning training purposes. Performed audio segmentation, timestamping, and tagging of speech and non-speech elements. Reviewed and corrected speech-to-text transcriptions for accuracy and speaker differentiation. Evaluated audio quality including background noise, clarity, and pronunciation. Ensured strict adherence to annotation guidelines and maintained high accuracy standards.

Labeled and categorized audio datasets for machine learning training purposes. Performed audio segmentation, timestamping, and tagging of speech and non-speech elements. Reviewed and corrected speech-to-text transcriptions for accuracy and speaker differentiation. Evaluated audio quality including background noise, clarity, and pronunciation. Ensured strict adherence to annotation guidelines and maintained high accuracy standards.

2023

Quality Assurance Tester / Content Reviewer

Label StudioTextEvaluation Rating

Conducted structured reviews of labeled transcript datasets to ensure accuracy and compliance with standards. Verified formatting, speaker alignment, and adherence to style guides before submission. Reported errors and verified data quality for AI training pipelines. • Reviewed and corrected transcript alignment • Ensured annotation and formatting consistency • Reported bugs and misclassifications • Met deadlines for quality assurance cycles

Conducted structured reviews of labeled transcript datasets to ensure accuracy and compliance with standards. Verified formatting, speaker alignment, and adherence to style guides before submission. Reported errors and verified data quality for AI training pipelines. • Reviewed and corrected transcript alignment • Ensured annotation and formatting consistency • Reported bugs and misclassifications • Met deadlines for quality assurance cycles

2023 - 2024

Education

Work History