Alexander Edmund

Key Skills

Software

AWS SageMaker

Appen

Axiom AI

Clickworker

CloudFactory

Data Annotation Tech

Deep Systems

Google Cloud Vertex AI

V7 Labs

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Geospatial Tiled Imagery

Video

Top Task Types

Action Recognition

Bounding Box

Classification

Emotion Recognition

Point Key Point

Freelancer Overview

I am a versatile AI training and data labeling specialist with expertise in natural language processing (NLP), image and video annotation, and user interface content evaluation. My experience includes bounding box labeling for e-commerce product images, video data annotation for the NFL by identifying player actions, and voice recording annotation for Meta. I bring strong attention to detail, consistency, and adherence to labeling guidelines, ensuring high-quality outputs that improve AI model performance. In addition to text, image, and video annotation, I have hands-on experience with web and mobile app usability reviews, providing structured feedback to optimize user experiences. My background in web development and e-commerce platforms enables me to understand both the technical and user perspectives, making me highly adaptable across different AI training projects. Passionate about advancing cutting-edge AI systems, I approach every project with precision, efficiency, and a commitment to excellence.

Labeling Experience

NFL Player Action Video Annotation

V7 LabsVideoBounding BoxEntity Ner Classification

Annotated large-scale NFL game footage to identify and classify player actions such as passing, running, tackling, and catching. Applied bounding boxes to accurately locate players in each frame and tracked movements across sequences. Ensured precise alignment of labeled actions with game timelines to support AI model training for sports analysis. Maintained strict adherence to annotation guidelines, achieving consistent labeling quality above 98% accuracy through peer reviews and spot checks.

Annotated large-scale NFL game footage to identify and classify player actions such as passing, running, tackling, and catching. Applied bounding boxes to accurately locate players in each frame and tracked movements across sequences. Ensured precise alignment of labeled actions with game timelines to support AI model training for sports analysis. Maintained strict adherence to annotation guidelines, achieving consistent labeling quality above 98% accuracy through peer reviews and spot checks.

2024 - 2025

Voice Recording Annotation for Meta

Internal Proprietary ToolingAudioAudio Recording

Performed large-scale annotation and evaluation of voice recordings for Meta’s speech recognition and NLP model training. Tasks included validating audio quality, classifying speaker intent, annotating linguistic features, and rating accuracy of speech-to-text outputs. Ensured annotations met strict linguistic and technical guidelines, achieving accuracy scores consistently above 97%. Contributed to training multilingual and accent-robust speech recognition systems for global deployment.

Performed large-scale annotation and evaluation of voice recordings for Meta’s speech recognition and NLP model training. Tasks included validating audio quality, classifying speaker intent, annotating linguistic features, and rating accuracy of speech-to-text outputs. Ensured annotations met strict linguistic and technical guidelines, achieving accuracy scores consistently above 97%. Contributed to training multilingual and accent-robust speech recognition systems for global deployment.

2023 - 2024

Education

Work History