Emmanuel K.

Key Skills

Software

Other

Telus

Appen

Top Subject Matter

AI response evaluation

instruction compliance

bias and ethics review

Top Data Types

Text

Document

Top Task Types

Data Collection

Classification

Freelancer Overview

AI Data Specialist (Generalist Focus) at Defined.ai. Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other, Telus, and Appen. Education includes Bachelor of Science, University of Port Harcourt (2023) and Postgraduate Certification, University of Port Harcourt (2026). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

AI Data Specialist (Generalist Focus) - Defined

AppenTextClassification

AI Data Specialist responsible for evaluating AI-generated outputs for accuracy, relevance, tone, and adherence to complex instructions and guidelines. The role required strong language understanding, intent classification, and quality assurance judgment to ensure consistent human-in-the-loop review. You contributed to dataset quality improvements by reviewing annotations and flagging bias, ambiguity, and ethical risks. • Evaluated AI responses for quality, correctness, and instruction compliance. • Reviewed and corrected annotated datasets to maintain consistency and fairness. • Identified potential bias and ethical risks, escalating issues for calibration. • Provided structured feedback to improve AI system behavior and alignment.

2024 - 2025

AI Data Specialist (Generalist Focus) at Defined.ai

OtherText

Evaluated AI-generated outputs for accuracy, relevance, tone, and compliance with detailed instructions and guidelines. Reviewed annotated datasets to ensure consistency, fairness, and guideline adherence while providing structured feedback for improvement. Flagged bias, ambiguity, and ethical risks in AI responses during quality calibration activities. • Assessed language understanding, intent classification, and response quality against rubric guidelines. • Performed dataset review and correction to improve annotation consistency and fairness. • Produced actionable feedback to support AI system behavior improvements. • Collaborated with distributed teams on quality calibration exercises.

2024 - 2025

Data Annotator at One Forma

OtherTextData Collection

Annotated and reviewed text, voice, and conversational data to support AI model training with a focus on accuracy and consistency. Followed detailed annotation guidelines, identified errors and edge cases, and ensured confidentiality while completing quality checks. Managed multiple tasks efficiently and delivered reliable annotated datasets within tight deadlines. • Labeled conversational and text data according to predefined instructions and quality standards. • Conducted quality checks to detect ambiguities and inconsistencies. • Maintained confidentiality and privacy practices during annotation work. • Handled high-throughput annotation while meeting delivery timelines.

2022 - 2024

AI Rater / Content Evaluator at TELUS International AI

TelusTextClassification

Rated search results, text outputs, and AI responses based on relevance and usefulness. Performed user-intent classification and language understanding tasks, and assessed AI-generated content against predefined quality standards. Maintained high accuracy while meeting productivity targets in a continuous evaluation workflow. • Evaluated outputs using rubric-based quality and relevance criteria. • Completed intent classification and language understanding checks. • Measured content against predefined guidelines for quality assurance. • Balanced accuracy requirements with throughput expectations.

2021 - 2022

AI Language & Content Evaluator (Freelance) at Appen

AppenTextClassification

Evaluated conversational AI responses for coherence, tone, and correctness according to task guidelines. Reviewed text classification outputs and alignment tasks to ensure consistency with expected labels and criteria. Ensured adherence to data privacy and ethical guidelines throughout the evaluation process. • Assessed conversational response quality including tone and correctness. • Verified text classification outputs and alignment task results. • Followed privacy and ethical requirements during reviews. • Applied consistent judgment across evaluation batches.

2018 - 2020

Education

Work History