Ademola O.

Key Skills

Software

Telus

Appen

Top Subject Matter

AI evaluation

quality review

and relevance assessment for ML/AI model outputs

Top Data Types

Text

Video

Document

Top Task Types

Classification

Freelancer Overview

AI Evaluation & Quality Review Specialist at TELUS DIGITAL (Remote). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Telus, Appen, and Outlier AI. Education includes Higher National Diploma, Federal Polytechnic Ilaro (2023) and Ordinary National Diploma, The Federal Polytechnic Ilaro (2020). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

AI Evaluation & Quality Review Specialist at TELUS DIGITAL (Remote)

TelusText

Conducted AI evaluation and quality assurance reviews of AI-generated outputs including responses, search results, and related digital content. Assessed outputs for accuracy, relevance, helpfulness, and compliance with project requirements and quality standards. Logged findings, identified inconsistencies or errors, and supported corrective feedback loops for improved model behavior. • Reviewed AI-generated responses for correctness and relevance • Evaluated search results and digital content quality • Identified inconsistencies, errors, and guideline deviations • Provided corrective feedback aligned to project requirements

2026 - Present

AI Evaluation & Data Labeling Specialist at Outlier AI (Remote)

TextClassification

Completed high-quality data labeling and annotation work to support machine learning and AI model training processes. Evaluated AI-generated responses for accuracy, relevance, and helpfulness against predefined quality standards. Conducted structured data review and classification across text-based datasets to enhance model understanding and performance. • Labeled and annotated training data for ML/AI pipelines • Assessed AI responses for quality (accuracy/relevance/helpfulness) • Classified and reviewed entries within text-based datasets • Ensured alignment with established labeling and evaluation standards

2025 - 2025

AI Evaluation & Data Annotation Specialist at Appen (Remote)

AppenTextClassification

Performed AI evaluation and data annotation tasks to support machine learning model training workflows. Reviewed and validated dataset examples to ensure accuracy, consistency, and compliance with established annotation guidelines and industry standards. Analyzed dataset quality to reduce noise and improve reliability of training data for downstream model performance. • Reviewed and validated labeled/annotated dataset entries • Checked consistency and guideline compliance • Conducted dataset analysis to improve training data quality • Ensured timely, efficient QA and annotation delivery

2025 - 2025

Education

Work History