Nomsa Phiri

Key Skills

Software

Labelbox

Scale AI

Surge AI

Telus

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Audio Recording

Classification

Evaluation/Rating

Prompt + Response Writing (SFT)

Question Answering

Freelancer Overview

I am an experienced AI Training and Data Annotation Specialist with a strong focus on evaluating images, videos, and text to improve AI accuracy and contextual understanding. I have hands-on experience labeling customer interactions, transaction data, and multimedia content to enhance chatbot performance, recommendation systems, and automated workflows. My work emphasizes precision, consistency, and adherence to project guidelines, ensuring high-quality datasets for AI training. I am skilled in reviewing and analyzing complex data, identifying patterns, and providing actionable insights to optimize AI models. With a background in customer service, technical support, and data handling, I bring a unique combination of analytical thinking, attention to detail, and domain knowledge, making me well-suited for diverse AI training and data labeling projects.

Labeling Experience

Image & Video Annotation for AI Evaluation

AppenImageBounding BoxClassification

Reviewed and labeled images and videos for AI training projects, including object recognition, scene classification, and action tracking. Tasks included applying bounding boxes, polygons, segmentation masks, and other annotations to ensure high-quality datasets. Evaluated AI predictions against labeled data to provide feedback and improve model accuracy. The project emphasized precision, consistency, and adherence to annotation guidelines across large volumes of multimedia content.

Reviewed and labeled images and videos for AI training projects, including object recognition, scene classification, and action tracking. Tasks included applying bounding boxes, polygons, segmentation masks, and other annotations to ensure high-quality datasets. Evaluated AI predictions against labeled data to provide feedback and improve model accuracy. The project emphasized precision, consistency, and adherence to annotation guidelines across large volumes of multimedia content.

2018

Education

Work History