Dylan Hussey

Key Skills

Software

Data Annotation Tech

Top Subject Matter

No subject matter listed

Top Data Types

Text

Video

Image

Audio

Top Label Types

Prompt Response Writing SFT

Evaluation Rating

Freelancer Overview

I have hands-on experience working with Data Annotation Tech, contributing to AI training datasets through structured data labeling, content evaluation, and guideline-based task completion. In this role, I applied detailed annotation frameworks to assess language quality, relevance, and accuracy while maintaining consistency across high-volume tasks. I am comfortable interpreting complex instructions, identifying subtle distinctions in tone and intent, and delivering precise outputs with minimal supervision. My work required strong pattern recognition, sustained focus, and careful judgment to ensure reliable model training inputs. In addition to my annotation experience, my professional background in e-commerce analytics and operations has strengthened my ability to manage large datasets, maintain quality standards, and work independently in fast-paced environments. My academic foundation in Women’s, Gender & Sexuality Studies and Creative Writing further supports my ability to evaluate bias, nuance, and linguistic clarity—skills that are essential for high-quality AI training and content review.

Labeling Experience

Audio Evaluation for AI Training

Data Annotation TechAudioEvaluation Rating

Evaluated audio-based AI model outputs for speech and multimodal training projects using structured rating guidelines. Assessed transcription accuracy, speech clarity, contextual understanding, instruction adherence, and safety alignment while maintaining consistency and quality across high-volume datasets.

Evaluated audio-based AI model outputs for speech and multimodal training projects using structured rating guidelines. Assessed transcription accuracy, speech clarity, contextual understanding, instruction adherence, and safety alignment while maintaining consistency and quality across high-volume datasets.

2025

Image Data Annotation & Quality Assessment

Data Annotation TechImageEvaluation Rating

Evaluated image-based AI model outputs for computer vision and multimodal training projects using structured rating guidelines. Assessed visual accuracy, object recognition, contextual relevance, instruction adherence, and safety alignment while maintaining high consistency and quality across large datasets.

Evaluated image-based AI model outputs for computer vision and multimodal training projects using structured rating guidelines. Assessed visual accuracy, object recognition, contextual relevance, instruction adherence, and safety alignment while maintaining high consistency and quality across large datasets.

2025

Video Evaluation for Multimodal AI Training

Data Annotation TechVideoEvaluation Rating

Evaluated video-based AI model outputs for multimodal training projects using structured guidelines and rating frameworks. Assessed scene understanding, action recognition, contextual accuracy, instruction adherence, and safety alignment. Maintained high consistency and accuracy across large task volumes while applying calibrated judgment to nuanced or ambiguous cases.

Evaluated video-based AI model outputs for multimodal training projects using structured guidelines and rating frameworks. Assessed scene understanding, action recognition, contextual accuracy, instruction adherence, and safety alignment. Maintained high consistency and accuracy across large task volumes while applying calibrated judgment to nuanced or ambiguous cases.

2025

LLM Evaluation

Data Annotation TechTextPrompt Response Writing SFT

Contribute to ongoing LLM training projects focused on prompt and response writing (SFT) and structured evaluation workflows. Craft high-quality prompts and model outputs aligned with detailed guidelines, and assess AI responses for instruction adherence, reasoning quality, safety alignment, coherence, and factual consistency. Maintain accuracy and consistency across high-volume tasks while applying calibrated judgment to nuanced or ambiguous cases in generative and multimodal AI systems.

Contribute to ongoing LLM training projects focused on prompt and response writing (SFT) and structured evaluation workflows. Craft high-quality prompts and model outputs aligned with detailed guidelines, and assess AI responses for instruction adherence, reasoning quality, safety alignment, coherence, and factual consistency. Maintain accuracy and consistency across high-volume tasks while applying calibrated judgment to nuanced or ambiguous cases in generative and multimodal AI systems.

2025

Education

Work History