Erica Malambu

Key Skills

Software

Data Annotation Tech

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Classification

Evaluation Rating

Transcription

Freelancer Overview

I am an analytical content evaluator with experience reviewing AI-generated text for accuracy and relevance. Additionally, I am skilled in comparing model responses, as well as identifying tonal inconsistencies and applying structured guidelines to improve AI training data quality. My background in English Literature and Language supports strong linguistic judgement and critical analysis of language-based outputs, and allows me to assess not only objective instruction following and factual accuracy, but also the quality of visual, creative, and rhetorical elements. I am sensitive to nuance in language and assess ambiguity in interpretation and judgement.

Labeling Experience

AI Text Annotation and Evaluation

Data Annotation TechTextClassificationEvaluation Rating

I annotated and evaluated AI-generated text outputs using structured guidelines. Some tasks included classification of responses, quality evaluation and rating across multiple dimensions such as factuality, coherence, verbosity, and transcript of audio but mainly text where required. Additionally, this included comparing multiple model outputs or a thread of outputs across dimensions such as following instructions across multiple counts, and identifying quality issues to support improvement of large language model training datasets. This work required careful guideline adherence and attention to detail.

I annotated and evaluated AI-generated text outputs using structured guidelines. Some tasks included classification of responses, quality evaluation and rating across multiple dimensions such as factuality, coherence, verbosity, and transcript of audio but mainly text where required. Additionally, this included comparing multiple model outputs or a thread of outputs across dimensions such as following instructions across multiple counts, and identifying quality issues to support improvement of large language model training datasets. This work required careful guideline adherence and attention to detail.

2025 - 2025

Education

Work History