Whilky Ogolla

I’m a Computer Science graduate with 4+ years of experience in AI training data, audio annotation, and quality evaluation. I bring strong auditory perception across many accents, including native East African English (Kenyan accent), with deep awareness of tonal stress patterns, vowel qualities, and prosodic features.

In my work, I transcribe and label speech data—marking disfluencies, evaluating speech quality, and performing accent identification—while adhering to annotation guideline adherence and scoring frameworks. I’ve completed audio annotation, transcription, and speech labeling tasks via Appen and Google Crowdsource, supporting RLHF workflows and AI output quality review.

I also focus heavily on data quality assurance. At AMREC, I validated and reviewed datasets collected via ODK, SurveyCTO, CommCare, and KoboToolbox, identified errors and inconsistencies, and produced structured quality reports for research and AI training pipelines.

Before that, I supported digital data documentation and ICT systems at KEMRI and completed high-accuracy data entry and cross-verification at IEBC. I’m detail-oriented, fluent in English, and available remotely on a flexible basis, with a collaborative, remote & async mindset—and I mentor junior annotators on evaluation guidelines and documentation best practices.