Annie Chikaonda

Key Skills

Software

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Image

Video

Top Label Types

Bounding Box

Polygon

Point Key Point

Classification

Text Generation

Segmentation

Object Detection

Action Recognition

Freelancer Overview

I am an experienced data annotator with a strong background in data labeling for image, audio, text, and video projects, gained through my work as an AI Annotator at Appen CloudGen. My responsibilities included creating interleaved video conversations, expanding scenes, attaching product information to images, and transcribing multimedia content, giving me hands-on exposure to a variety of AI training data tasks across computer vision and natural language processing domains. I am highly proficient in digital tools such as Excel, SPSS, EMT manufacturing software, and Microsoft Office, and I bring strong analytical, quality management, and communication skills from my laboratory and teaching experience. I am detail-oriented, quick to adapt to new challenges, and able to work efficiently both independently and as part of a team.

Labeling Experience

Image Data labeling

AppenImageBounding BoxPolygon

Appen – Image Labeling & Annotation Project (2025) Contributed to a large-scale image annotation project supporting AI and machine-learning models in computer vision. Performed bounding box and polygon annotations, semantic segmentation, image classification, keypoint labeling, and attribute tagging using Appen’s annotation tools. Worked with high-volume datasets across diverse environments while following strict annotation guidelines. Maintained high accuracy through quality assurance checks, qualification tests, and reviewer feedback, in compliance with data privacy and ethical AI standards.

Appen – Image Labeling & Annotation Project (2025) Contributed to a large-scale image annotation project supporting AI and machine-learning models in computer vision. Performed bounding box and polygon annotations, semantic segmentation, image classification, keypoint labeling, and attribute tagging using Appen’s annotation tools. Worked with high-volume datasets across diverse environments while following strict annotation guidelines. Maintained high accuracy through quality assurance checks, qualification tests, and reviewer feedback, in compliance with data privacy and ethical AI standards.

2025 - 2025

Video labeling Project

AppenVideoBounding BoxPoint Key Point

In 2024, Appen video labeling projects involved contributors watching short video clips and annotating key objects, actions, or events across frames, for example tracking moving objects and labeling activities like ‘person walking’ or ‘car turning’ to generate training data for computer vision models in applications such as autonomous navigation or surveillance

In 2024, Appen video labeling projects involved contributors watching short video clips and annotating key objects, actions, or events across frames, for example tracking moving objects and labeling activities like ‘person walking’ or ‘car turning’ to generate training data for computer vision models in applications such as autonomous navigation or surveillance

2024 - 2024

Education

Work History