SamNyambura

Data Annotator

CVAT.AI • Freelance

Oct 2024 - Nov 2025 • 1 yr 1 mo

As an Experienced Data Annotator and AI Data Trainer, I’ve collaborated with global teams to deliver accurate, context-aware, and high-quality datasets critical to AI model development. My background as a Freelance AI Tutor allows me to simplify complex AI concepts for learners and professionals looking to break into the AI space. Roles and Responsibilities: 1. Annotated and labeled diverse datasets, including images, video, audio, and text, according to project-specific guidelines. 2. Performed video segmentation and action labeling, aligning audio-to-video data to support multimodal AI and speech recognition models. 3. Categorized and tagged image datasets with precision, ensuring accuracy for computer vision training. 4. Transcribed and annotated audio data, enhancing dataset quality for speech-to-text and NLP applications. 5. Reviewed and evaluated AI outputs on text-based tasks, verifying accuracy, intent alignment, and cultural appropriateness. 6. Conducted prompt-based annotation reviews to refine LLM performance for clarity, correctness, and contextual relevance. 7. Performed rigorous quality assurance checks across all data types, maintaining consistency and high accuracy for scalable AI training.

Data Annotator

Adept Technologies Kenya • Freelance

Mar 2023 - Mar 2024 • 1 yr

As a detail-oriented Data Annotation Specialist, I bring a sharp eye for detail, a strong command of structured classification systems, and a commitment to precision in high-volume, quality-sensitive environments. My work supports data integrity and consistency across complex visual datasets, where accuracy and collaboration are critical. I thrive in roles that demand both speed and meticulousness, consistently exceeding performance benchmarks while ensuring outputs meet rigorous quality standards. Roles and Responsibilities: 1. Specialized in annotating and segmenting images of food leftovers to support AI research in sustainability and waste management. 2. Applied detailed taxonomies and labeling instructions to differentiate between types of food, packaging, and organic matter. 3. Collaborated with QA leads and team members to validate labels and ensure consistency across the dataset. 4. Conducted manual quality checks on annotated images to detect and correct labeling errors before final submission. 5. Adhered to daily productivity targets while maintaining over 95% accuracy in labeling outcomes.