Benita Adieme

Key Skills

Software

Appen

Telus

Mercor

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Label Types

Classification

Evaluation Rating

Fine Tuning

Freelancer Overview

I am an experienced AI response evaluator and search quality analyst with over three years of hands-on work in data annotation and training data evaluation for leading platforms like Appen, TELUS International, and Mercor. My background includes rating AI-generated outputs, assessing search engine results, and applying structured quality criteria to improve large language models and AI systems. I excel at interpreting user intent, analyzing empathy and tone, and ensuring outputs meet high standards for relevance, clarity, and appropriateness—skills especially relevant to NLP and conversational AI domains. I am highly skilled in using CRM tools such as HubSpot and Zoho, as well as the Microsoft Office Suite and Google Workspace, and have a proven track record of delivering accurate, consistent assessments in remote, independent contractor roles. My academic foundation in Information Technology and my experience across diverse, high-volume projects enable me to bring both analytical rigor and strong communication to every data labeling and annotation task.

Labeling Experience

Search Quality Analyst & AI Content Evaluator

TelusTextClassificationEvaluation Rating

Assessed search result quality, content relevance, and user experience signals for AI system training datasets across diverse query categories and languages for TELUS International since 2022. Applied nuanced judgment to evaluate sensitive and complex queries — including those requiring empathy, cultural awareness, and an understanding of user wellbeing — ensuring high-quality labeling output for enterprise AI data projects. Maintained strict adherence to confidentiality requirements and quality benchmarks throughout.

Assessed search result quality, content relevance, and user experience signals for AI system training datasets across diverse query categories and languages for TELUS International since 2022. Applied nuanced judgment to evaluate sensitive and complex queries — including those requiring empathy, cultural awareness, and an understanding of user wellbeing — ensuring high-quality labeling output for enterprise AI data projects. Maintained strict adherence to confidentiality requirements and quality benchmarks throughout.

2022

Search Engine & AI Data Evaluation Specialist

AppenTextClassificationEvaluation Rating

Continuously evaluated Search Engine Results Pages (SERPs) for relevance, accuracy, and quality against detailed project guidelines for Appen since 2022. Applied structured scoring rubrics across thousands of evaluations, maintaining high inter-rater reliability and quality standards required by leading AI labs. Interpreted user search intent behind queries and assessed how well results satisfied the underlying information need — skills directly transferable to evaluating AI-generated content for appropriateness, emotional alignment, and contextual accuracy.

Continuously evaluated Search Engine Results Pages (SERPs) for relevance, accuracy, and quality against detailed project guidelines for Appen since 2022. Applied structured scoring rubrics across thousands of evaluations, maintaining high inter-rater reliability and quality standards required by leading AI labs. Interpreted user search intent behind queries and assessed how well results satisfied the underlying information need — skills directly transferable to evaluating AI-generated content for appropriateness, emotional alignment, and contextual accuracy.

2022

Audio Similarity Evaluator & AI Voice Detection Specialist

MercorAudioClassificationEvaluation Rating

Performed dedicated audio data labeling and evaluation tasks on the Mercor platform in 2025. Work involved listening carefully to pairs of audio clips and identifying which sample sounded most similar to a provided reference recording. Additionally evaluated audio content to determine whether it was naturally produced by a human or synthetically generated by AI — contributing directly to voice AI training pipelines, audio similarity model development, and synthetic speech detection datasets. Applied consistent perceptual listening judgment and close attention to tonal, rhythmic, and quality-based audio cues throughout all tasks.

Performed dedicated audio data labeling and evaluation tasks on the Mercor platform in 2025. Work involved listening carefully to pairs of audio clips and identifying which sample sounded most similar to a provided reference recording. Additionally evaluated audio content to determine whether it was naturally produced by a human or synthetically generated by AI — contributing directly to voice AI training pipelines, audio similarity model development, and synthetic speech detection datasets. Applied consistent perceptual listening judgment and close attention to tonal, rhythmic, and quality-based audio cues throughout all tasks.

2025 - 2025

Multimodal AI Content Evaluator — Audio, Video & Image

MercorVideoClassificationFine Tuning

Worked as a multimodal AI content evaluator for Mercor in 2025, performing pairwise comparison tasks across audio, video, and image data types. Tasks involved listening to pairs of audio clips and identifying which sounded more similar to a provided reference sample, as well as reviewing pairs of videos and images to assess which appeared more natural and realistic versus AI-generated. Applied consistent perceptual judgment and attention to detail to deliver accurate, calibrated evaluations that directly supported AI model training and synthetic media detection pipelines.

Worked as a multimodal AI content evaluator for Mercor in 2025, performing pairwise comparison tasks across audio, video, and image data types. Tasks involved listening to pairs of audio clips and identifying which sounded more similar to a provided reference sample, as well as reviewing pairs of videos and images to assess which appeared more natural and realistic versus AI-generated. Applied consistent perceptual judgment and attention to detail to deliver accurate, calibrated evaluations that directly supported AI model training and synthetic media detection pipelines.

2025 - 2025

Education

Work History