Penny Sue

Key Skills

Software

Tagtog

V7 Labs

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

Document

Image

Text

Video

Top Task Types

RLHF

Fine-tuning

Function Calling

Prompt + Response Writing (SFT)

Audio Recording

Freelancer Overview

I am an experienced English-language specialist with over 8 years in editorial review, AI content evaluation, and academic research. My expertise includes evaluating and annotating AI-generated responses, developing prompt-response sets, and scoring outputs using structured rubrics to ensure clarity, factual accuracy, and adherence to editorial standards. I have worked extensively with tools such as Microsoft 365, Google Workspace, and various research databases, and am highly skilled in fact-checking, logical reasoning, and structured justification writing. My background spans multiple domains, and I have contributed to key projects in AI fine-tuning, summarization, classification, and quality assurance, consistently improving dataset reliability and supporting high-quality model training. I thrive in remote, project-based environments and am adept at quickly adapting to new topics and guidelines.

Labeling Experience

LLM Response Evaluation and RLHF Annotation Project

TagtogTextRLHFFine Tuning

Assessed on 5,500 AI responses for clarity, accuracy, safety, and relevance. Rated the outputs using rubrics and wrote justifications for each rating. Identified inaccuracies, inconsistencies, and policy violations. Conducted fact-checking using credible sources in academia and industry. Developed and refined pairs of prompts and responses for AI fine-tuning (SFT). Supported the RLHF process by rating responses and selecting the best outputs. Adhered to high standards of quality and accuracy.

Assessed on 5,500 AI responses for clarity, accuracy, safety, and relevance. Rated the outputs using rubrics and wrote justifications for each rating. Identified inaccuracies, inconsistencies, and policy violations. Conducted fact-checking using credible sources in academia and industry. Developed and refined pairs of prompts and responses for AI fine-tuning (SFT). Supported the RLHF process by rating responses and selecting the best outputs. Adhered to high standards of quality and accuracy.

2022 - 2024

Education

Work History