Ashley Mcfadin

Key Skills

Software

Labelbox

Scale AI

Supervisely

CVAT

LabelImg

Prodigy

Doccano

Mercor

SuperAnnotate

Top Subject Matter

Computer Vision

Natural Language Processing

Multimodal ML

Top Data Types

Image

Audio

Text

Top Task Types

Object Detection

Transcription

Bounding Box

Polygon

Classification

Entity (NER) Classification

Point/Key Point

Text Generation

Question Answering

Text Summarization

Fine-tuning

Data Collection

Function Calling

Prompt + Response Writing (SFT)

Freelancer Overview

Data Labeling Specialist. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox, Scale AI, and Supervisely. Education includes Bachelor of Social Work, University of Arkansas (2023) and Certificate, Gallaudet University (2023). AI-training focus includes data types such as Image and Audio and labeling workflows including Object Detection and Transcription.

Labeling Experience

Data Labeling Specialist

LabelboxImageObject Detection

Led annotation projects for over 100,000 images, focusing on object detection and instance segmentation tasks. Enhanced model performance through detailed guidelines, rigorous QA, and improved annotation processes. Managed team training and the development of project resources for consistent, high-quality labeling. • Designed annotation pipelines and reduced annotation disputes by 40%. • Implemented multi-stage QA, increasing label accuracy from 86% to 96% within three months. • Trained and onboarded a 25-person remote labeling team with custom materials and quizzes. • Automated data conversion and streamlined dataset delivery, reducing manual work by 70%.

Led annotation projects for over 100,000 images, focusing on object detection and instance segmentation tasks. Enhanced model performance through detailed guidelines, rigorous QA, and improved annotation processes. Managed team training and the development of project resources for consistent, high-quality labeling. • Designed annotation pipelines and reduced annotation disputes by 40%. • Implemented multi-stage QA, increasing label accuracy from 86% to 96% within three months. • Trained and onboarded a 25-person remote labeling team with custom materials and quizzes. • Automated data conversion and streamlined dataset delivery, reducing manual work by 70%.

2025 - Present

Generalist/ QA Expert

LabelboxAudioTranscription

Performed audio transcription alignment and sentiment annotation for multi-modal machine learning projects. Ensured high throughput and maintained QA scores above industry standards. Built tools and dashboards for tracking annotation metrics and delivering insights to clients. • Completed various multi-modal labeling tasks, including video object tracking. • Maintained throughput targets and QA scores above 95%. • Developed lightweight dashboards for annotation KPI tracking. • Supported continuous improvement of annotation workflows and client reporting.

Performed audio transcription alignment and sentiment annotation for multi-modal machine learning projects. Ensured high throughput and maintained QA scores above industry standards. Built tools and dashboards for tracking annotation metrics and delivering insights to clients. • Completed various multi-modal labeling tasks, including video object tracking. • Maintained throughput targets and QA scores above 95%. • Developed lightweight dashboards for annotation KPI tracking. • Supported continuous improvement of annotation workflows and client reporting.

2025 - 2026

Education

Work History