Beth G.

Key Skills

Software

No software listed

Top Subject Matter

AI response evaluation and language model quality assurance

Natural language annotation (intent, sentiment, relevance)

LLM evaluation

Top Data Types

Text

Top Task Types

Classification

Freelancer Overview

AI Response Reviewer (Remote, 2022-2023). Core strengths include N and A. Education includes Master of Science, University of Arts (2017) and Bachelor of Science, University of Nairobi (2021). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

AI Trainer (Remote, 2023-Present)

Text

Evaluated and ranked AI-generated responses based on accuracy, relevance, reasoning quality, and safety. Identified factual errors, logical inconsistencies, and hallucinations in model outputs to support model improvement. Wrote and refined clear, constraint-based prompts to test model behavior across multiple tasks. Applied rubric-based scoring and provided detailed justifications for ratings while adhering to strict task instructions and formatting rules. • Response ranking by quality and safety • Hallucination and inconsistency detection • Prompt writing for behavioral testing • Rubric scoring with justification and guideline compliance

2023 - Present

AI Response Reviewer (Remote, 2022-2023)

Text

Evaluated AI-generated responses for accuracy, completeness, clarity, and reasoning quality through structured assessment. Conducted side-by-side comparisons of multiple model outputs to select the best responses for given tasks. Identified hallucinations, unsupported claims, and instruction-following errors and provided actionable feedback to improve future performance. • Accuracy and completeness review • Clarity and reasoning quality scoring • Best-response selection across model comparisons • Hallucination and instruction-following error flagging

2022 - 2023

Data Annotator & Labeling Specialist (Remote, 2021-2022)

TextClassification

Performed data annotation and labeling of text for AI and machine learning model training under detailed guidelines. Carried out intent classification, relevance tagging, sentiment labeling, and content categorization as part of the labeling workflow. Reviewed outputs to detect inaccuracies, bias, and low-quality responses, ensuring consistency across large datasets. • Intent classification • Relevance tagging • Sentiment labeling • Content categorization and quality checks

2021 - 2022

Education

Work History