Jordan R.

Key Skills

Software

Label Studio

Sama

CVAT

Top Subject Matter

Computer Vision (Object Detection) and NLP data labeling for global tech clients (OpenAI, Google, Meta).

Natural Language Processing dataset annotation and AI training for global tech clients.

Academic AI data annotation pipelines

Top Data Types

Text

Image

Top Task Types

Object Detection

Entity (NER) Classification

Freelancer Overview

AI Trainer & Senior Data Annotator (Scale AI Company). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Label Studio, Sama, and CVAT. Education includes Bachelor of Science, American National University (2022) and Google Data Analytics Professional Certificate, Coursera (2023). AI-training focus includes data types such as Images, Text, and Computer Code and labeling workflows including Object Detection, Entity (NER) Classification, and Computer Programming.

Labeling Experience

AI Trainer & Senior Data Annotator (Scale AI Company)

SamaTextEntity (NER) Classification

Provided AI training and data labeling supervision for NLP datasets, ensuring high-quality text annotations for client model development. Managed annotation guideline enforcement and QA processes to maintain accuracy and reduce downstream errors. Coordinated with AI engineers to iteratively improve training datasets based on audit findings and performance needs. • Delivered 15,000+ high-quality labeled data points per sprint with 98% accuracy. • Reduced project error rates by 22% through developed annotation guidelines and QA rubrics. • Conducted daily quality audits and provided real-time feedback to annotators. • Applied LabelStudio and Sama’s internal platform for text labeling and QA under strict SLAs.

2023 - Present

AI Trainer & Senior Data Annotator (Scale AI Company)

Label StudioObject Detection

Trained and supervised a team of 12 junior annotators to label complex computer vision datasets for large tech clients. Conducted daily quality audits with real-time feedback and collaborated with AI engineers to refine training data for improved model performance. Achieved 98% annotation accuracy and delivered 15,000+ high-quality data points per sprint while meeting strict SLAs. • Developed and enforced annotation guidelines and QA rubrics that reduced project error rates by 22%. • Annotated images, video, text, and audio using internal workflows while ensuring consistent ground truth. • Supervised inter-annotator consistency and supported annotators with performance monitoring. • Used LabelStudio and Sama’s internal platform to execute labeling and QA activities at scale.

2023 - Present

Research Assistant – AI Data Annotation & Machine Learning (University of London)

CVAT

Managed labeling pipelines for AI data annotation using CVAT and Python scripts to process research datasets. Ensured consistent annotation quality through data cleaning, quality checks, and maintenance of inter-annotator agreement. Supported faculty by documenting annotation processes and contributing to baseline ML model training efforts for academic work. • Processed 8,000+ records while maintaining 96% inter-annotator agreement. • Managed labeling workflows using CVAT and automated steps with Python scripts. • Performed dataset curation tasks to meet rigorous research standards. • Assisted with documentation for academic publications and baseline model training.

2022 - 2023

Education

Work History