Kennedy Shy

Key Skills

Software

Scale AI

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Image

Top Label Types

Segmentation

Classification

Freelancer Overview

I am an experienced AI Training Specialist with over 5 years of hands-on expertise in data labeling, annotation, and quality assurance for machine learning projects. My background spans large-scale computer vision and NLP data annotation, including image segmentation, video multi-object tracking, OCR, and text labeling. I have delivered more than 500,000 accurately labeled images and video frames for domains such as autonomous vehicles, retail analytics, and smart surveillance, consistently maintaining 99%+ accuracy. Skilled in tools like CVAT, Labelbox, SuperAnnotate, and V7 Darwin, I excel at dataset preparation, workflow optimization, and collaborating with ML engineers to ensure high-quality training data. My commitment to detail and data integrity helps drive the success of AI model development across diverse applications.

Labeling Experience

Senior AI Training Specialist

Scale AIImageSegmentation

As Senior AI Training Specialist at Scale AI, I led annotation of large-scale computer vision datasets for autonomous vehicles and retail AI. I supervised junior labelers to ensure 99%+ accuracy in image and video annotations. I refined annotation guidelines, collaborated with ML engineers, and delivered over 500,000 labeled frames. • Performed semantic segmentation, polygon labeling, and multi-object tracking on high-volume video datasets. • Maintained dataset quality through continuous review and QA. • Ensured annotation workflow optimization and reduced error rates by 25%. • Supported model training readiness by aligning data with engineers’ requirements.

As Senior AI Training Specialist at Scale AI, I led annotation of large-scale computer vision datasets for autonomous vehicles and retail AI. I supervised junior labelers to ensure 99%+ accuracy in image and video annotations. I refined annotation guidelines, collaborated with ML engineers, and delivered over 500,000 labeled frames. • Performed semantic segmentation, polygon labeling, and multi-object tracking on high-volume video datasets. • Maintained dataset quality through continuous review and QA. • Ensured annotation workflow optimization and reduced error rates by 25%. • Supported model training readiness by aligning data with engineers’ requirements.

2022

AI Data Annotator

AppenImageClassification

As an AI Data Annotator at Appen, I conducted detailed image and video annotation for computer vision datasets. My work supported smart city monitoring, traffic detection, and e-commerce analytics projects. I also annotated OCR and text-based datasets for NLP model development, maintained consistent QA scores, and performed data audits. • Used CVAT and Labelbox for image and video labeling tasks. • Annotated millions of frames for high-volume computer vision projects. • Maintained QA scores of 98–100% over multiple projects. • Supported NLP tasks including OCR and text annotation.

As an AI Data Annotator at Appen, I conducted detailed image and video annotation for computer vision datasets. My work supported smart city monitoring, traffic detection, and e-commerce analytics projects. I also annotated OCR and text-based datasets for NLP model development, maintained consistent QA scores, and performed data audits. • Used CVAT and Labelbox for image and video labeling tasks. • Annotated millions of frames for high-volume computer vision projects. • Maintained QA scores of 98–100% over multiple projects. • Supported NLP tasks including OCR and text annotation.

2019 - 2021

Education

Work History