Ragen B.

Key Skills

Software

Mercor

Other

Appen

Top Subject Matter

LLM evaluation and training (instruction following)

AI data training and quality evaluation for human interaction understanding

Image emotion recognition dataset labeling

Top Data Types

Text

Video

Image

Document

Top Task Types

Prompt + Response Writing (SFT)

Emotion Recognition

Freelancer Overview

Mercor, Remote — Generalist Evaluator Expert. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Mercor, Other, and Appen. Education includes Bachelor of Fine Arts, Arizona State University (2022). AI-training focus includes data types such as Text, Video, and Image and labeling workflows including Prompt + Response Writing (SFT), Evaluation, and Rating.

Labeling Experience

CrowdGen by Appen, Remote — AI Data Trainer

AppenImageEmotion Recognition

Provided detailed image descriptions to train AI systems for recognizing human emotions. Ensured consistency and accuracy of labeled datasets used for machine learning. Supported dataset quality for emotion-focused perception tasks. • Image description writing for emotion recognition • Labeled dataset consistency verification • Accuracy checks for training readiness • Emotion-focused annotation quality assurance

2025 - Present

Outlier, Remote — AI Data Trainer

OtherVideo

Reviewed and evaluated short-form video content to ensure alignment with strict quality guidelines. Provided structured feedback intended to improve AI understanding of human interactions and behavior. Contributed to dataset development used for training and tuning AI systems. • Video quality guideline compliance checks • Behavior and interaction feedback for annotation improvement • Dataset contribution for model training/tuning • Consistency-focused evaluation within defined criteria

2025 - Present

Mercor, Remote — Generalist Evaluator Expert

MercorTextPrompt + Response Writing (SFT)

Developed prompts to train large language models for instruction following, clarity, and compliance. Created golden responses and scoring rubrics to benchmark model outputs and evaluate response quality against defined criteria. Provided structured feedback to improve accuracy, reliability, and overall model behavior. • Prompt engineering for LLM instruction-following • Golden response creation for evaluation baselines • Scoring rubric design for consistent grading • Structured evaluation feedback for model improvement

2025 - Present

Education

Work History