Kanini Eunice

I am a detail-oriented Data Annotator with over 3 years of experience in labeling images, text, and audio datasets for AI/ML training. My proven track record in quality assurance and workflow optimization has enabled me to deliver high-accuracy annotated datasets consistently. I am proficient in Google Workspace and various annotation tools such as Labelbox and RectLabel, which have been instrumental in my work.

During my tenure at Mindrift, I labeled and reviewed diverse datasets, ensuring over 95% accuracy per project guidelines. My role involved conducting quality assurance checks to identify and resolve discrepancies, thereby improving dataset reliability. I thrive in remote collaboration environments, working with global teams to meet tight deadlines while optimizing annotation workflows for faster project delivery.

At ADEC Kenya, I annotated over 10,000 data samples for AI model training, adhering to strict quality standards. I implemented quality control procedures that reduced errors by 15% and streamlined workflows, cutting project turnaround time by 20%. My commitment to maintaining high standards has earned me recognition as an accuracy champion across multiple projects.