Ashton H.

Key Skills

Software

Don't disclose

Top Subject Matter

Video content understanding for AI models (multiclass structured categorization).

Multimodal video datasets for language model training (quality-focused annotation and evaluation).

Bias detection and fairness evaluation using video annotation for AI systems.

Top Data Types

Video

Image

Text

Document

Top Task Types

Classification

Fine-tuning

Freelancer Overview

Senior Video Annotation Specialist | Google DeepMind (Contract, Remote). Core strengths include Don't disclose. Education includes Bachelor of Science, Stanford University (2022). AI-training focus includes data types such as Video and labeling workflows including Classification, Fine-tuning, and Evaluation.

Labeling Experience

Senior Video Annotation Specialist | Google DeepMind (Contract, Remote)

Don't discloseVideoClassification

Responsible for structured video understanding annotations across 15+ content categories for flagship models. Ensured high-quality labeling by interpreting guidelines, resolving ambiguities, and maintaining consistency at scale. Measured performance using accuracy and consistency metrics to drive continuous protocol improvements. • Processes 1,000+ videos weekly. • Achieved 99.2% accuracy rate in structured video analysis. • Improved team consistency by 40% through revised annotation protocols. • Mentored 12 junior annotators on complex guideline interpretation.

2023 - Present

AI Training Data Specialist | OpenAI (Remote)

Don't discloseVideoFine-tuning

Curated and annotated video clips to build multimodal datasets used for language model training. Evaluated 8,000+ video clips from multiple social and educational contexts while identifying ambiguous cases for follow-up. Collaborated with ML engineers to refine annotation schemas and reduce training errors. • Labeled 8,000+ video clips across social media, educational content, and explainer videos. • Flagged ambiguous content with 95% precision to reduce training issues. • Refined annotation schemas in collaboration with ML engineers. • Supported dataset quality checks for downstream training.

2023 - 2023

Research Annotator | Stanford HAI (Human-Centered AI Institute)

Don't discloseVideo

Annotated video content for human-centered research on bias detection in AI systems. Processed sensitive and diverse video materials while tracking quality metrics and detailed logs for multiple projects. Contributed to the research community by publishing work on video annotation methodologies. • Worked across 20+ research projects simultaneously with consistent documentation. • Maintained detailed logs and quality metrics for bias-detection objectives. • Conducted annotation on sensitive, diverse content for fairness analysis. • Co-authored 3 papers on video annotation methodologies.

2021 - 2022

Education