Peter Thompson

Key Skills

Software

Labelbox

CVAT

Prodigy

Top Subject Matter

AI Model Training Data

NLP Model Training Data

AI Text Annotation Project

Top Data Types

Text

Image

Top Task Types

Classification

Freelancer Overview

AI Data Labeling Specialist at Data AI Solutions. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox, CVAT, and Prodigy. Education includes Bachelor of Science, University of California (2020). AI-training focus includes data types such as Text and Image and labeling workflows including Classification.

Labeling Experience

AI Data Labeling Specialist at Data AI Solutions

LabelboxTextClassification

Labeled and validated text and image datasets for machine learning model training and evaluation. Ensured high accuracy and consistency while meeting strict project deadlines for multiple AI projects. Used advanced annotation platforms to categorize data according to predefined guidelines. • Annotated and labeled large volumes of data entries. • Reviewed AI-generated responses for accuracy and quality control. • Improved overall dataset quality through thorough validation processes. • Maintained 98% accuracy across multiple datasets.

Labeled and validated text and image datasets for machine learning model training and evaluation. Ensured high accuracy and consistency while meeting strict project deadlines for multiple AI projects. Used advanced annotation platforms to categorize data according to predefined guidelines. • Annotated and labeled large volumes of data entries. • Reviewed AI-generated responses for accuracy and quality control. • Improved overall dataset quality through thorough validation processes. • Maintained 98% accuracy across multiple datasets.

2022 - Present

Data Annotation Assistant at AI Research Lab

CVATTextClassification

Labeled and prepared training data for natural language processing models. Reviewed, cleaned, and organized structured datasets to ensure their suitability for machine learning workflows. Increased annotation efficiency by optimizing data labeling practices within the team. • Contributed to development of datasets for AI language models. • Checked datasets for errors and inconsistencies. • Organized structured data for enhanced model performance. • Collaborated on workflow improvements for greater efficiency.

Labeled and prepared training data for natural language processing models. Reviewed, cleaned, and organized structured datasets to ensure their suitability for machine learning workflows. Increased annotation efficiency by optimizing data labeling practices within the team. • Contributed to development of datasets for AI language models. • Checked datasets for errors and inconsistencies. • Organized structured data for enhanced model performance. • Collaborated on workflow improvements for greater efficiency.

2020 - 2022

Image Labeling Dataset (Relevant Project)

CVATImageClassification

Tagged and labeled thousands of images to support the training of computer vision models. Used annotation software to accurately identify and categorize visual data. Enhanced image dataset quality for machine learning model development. • Applied image labeling techniques such as tagging and classification. • Improved accuracy and metadata integrity for images. • Worked with large-scale image datasets for model training. • Ensured labeling adhered to project guidelines.

Tagged and labeled thousands of images to support the training of computer vision models. Used annotation software to accurately identify and categorize visual data. Enhanced image dataset quality for machine learning model development. • Applied image labeling techniques such as tagging and classification. • Improved accuracy and metadata integrity for images. • Worked with large-scale image datasets for model training. • Ensured labeling adhered to project guidelines.

2020 - 2020

AI Text Annotation Project (Relevant Project)

ProdigyTextClassification

Labeled and categorized large text datasets used specifically for training natural language AI models. Focused on organizing and annotating data to meet machine learning requirements. Ensured annotation met high-quality standards for language model tuning. • Labeling involved text classification and entity tagging. • Maintained data consistency and reduced errors in data. • Improved model outcomes through precise labeling. • Supported cross-team collaboration on NLP project data.

Labeled and categorized large text datasets used specifically for training natural language AI models. Focused on organizing and annotating data to meet machine learning requirements. Ensured annotation met high-quality standards for language model tuning. • Labeling involved text classification and entity tagging. • Maintained data consistency and reduced errors in data. • Improved model outcomes through precise labeling. • Supported cross-team collaboration on NLP project data.

2020 - 2020

Education

Work History