Abigael Johns

Key Skills

Software

Appen

Clickworker

CloudFactory

CrowdSource

CVAT

Data Annotation Tech

Labelbox

OneForma

Remotasks

SuperAnnotate

Toloka

Telus

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Text

Video

Top Task Types

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Classification

Entity Ner Classification

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Prompt Response Writing SFT

Freelancer Overview

I am a highly experienced Data Annotation and AI Training Specialist with over four years of hands-on experience in labeling diverse datasets for machine learning and artificial intelligence applications. My work spans image and video annotation, object detection, semantic segmentation, and 3D point cloud labeling using industry-standard tools such as CVAT, Labelbox, SuperAnnotate, and CloudCompare. I have successfully contributed to projects involving both 2D and 3D data, including LIDAR, ensuring high levels of accuracy and consistency while adhering to strict annotation guidelines and deadlines. My strengths lie in attention to detail, strong analytical thinking, and a deep understanding of annotation workflows and quality assurance in AI model training. I thrive in collaborative, remote team environments and am quick to adapt to new platforms and project requirements. My multidisciplinary background in applied mathematics further enhances my ability to interpret complex labeling tasks with precision and logic.

Labeling Experience

falcon3d

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I worked on a 3D data annotation project for Falcon 3D, focusing on annotating and classifying high-resolution geospatial data for AI training purposes. Using tools like CloudCompare and CVAT, I labeled LIDAR point clouds and photogrammetry data to support urban planning, object detection, and autonomous navigation systems. This involved identifying structures such as buildings, roads, vegetation, and utility lines across complex 3D environments

I worked on a 3D data annotation project for Falcon 3D, focusing on annotating and classifying high-resolution geospatial data for AI training purposes. Using tools like CloudCompare and CVAT, I labeled LIDAR point clouds and photogrammetry data to support urban planning, object detection, and autonomous navigation systems. This involved identifying structures such as buildings, roads, vegetation, and utility lines across complex 3D environments

2020 - 2022

Education

Work History