Emmanuel Aduyemi

Key Skills

Software

SuperAnnotate

Other

Top Subject Matter

General AI data annotation

General and technical LLMs

General AI evaluation

Top Data Types

Image

Video

Text

Audio

Document

Top Task Types

Prompt + Response Writing (SFT)

Classification

Transcription

Freelancer Overview

Generalist AI Annotator / Evaluator. Brings 7+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include SuperAnnotate and Other. Education includes Doctor of Medicine, Northeast Ohio Medical University (2025) and Master of Science, Kent State University (2024). AI-training focus includes data types such as Image, Video, and Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

Generalist AI Annotator / Evaluator

SuperannotateImage

As a Generalist AI Annotator / Evaluator at SuperAnnotate, I performed comprehensive annotation across multimodal datasets using strict project guidelines. I reviewed and evaluated AI-generated outputs for accuracy, reasoning clarity, and adherence to instructions. I created prompts to test model behavior, identified ambiguities, and maintained high annotation accuracy. • Annotated diverse data types including text, image, and video. • Evaluated nuanced correctness and reasoning in AI outputs. • Crafted and refined prompts to examine model responses. • Escalated ambiguous cases and edge findings via QA workflows.

As a Generalist AI Annotator / Evaluator at SuperAnnotate, I performed comprehensive annotation across multimodal datasets using strict project guidelines. I reviewed and evaluated AI-generated outputs for accuracy, reasoning clarity, and adherence to instructions. I created prompts to test model behavior, identified ambiguities, and maintained high annotation accuracy. • Annotated diverse data types including text, image, and video. • Evaluated nuanced correctness and reasoning in AI outputs. • Crafted and refined prompts to examine model responses. • Escalated ambiguous cases and edge findings via QA workflows.

2025 - Present

Data Annotation & AI Training Specialist (Freelance)

OtherTextPrompt Response Writing SFT

As a Data Annotation & AI Training Specialist (Freelance), I created realistic prompts and high-quality responses to benchmark LLM performance. I evaluated and edited AI outputs for factual accuracy, soundness, and usefulness. I generated prompt variations and used structured rubrics to produce consistent training data. • Crafted human-like prompts mirroring realistic user questions. • Authored model training data to improve LLMs. • Edited and reviewed AI outputs for quality control. • Evaluated and stress-tested model instruction sensitivity.

As a Data Annotation & AI Training Specialist (Freelance), I created realistic prompts and high-quality responses to benchmark LLM performance. I evaluated and edited AI outputs for factual accuracy, soundness, and usefulness. I generated prompt variations and used structured rubrics to produce consistent training data. • Crafted human-like prompts mirroring realistic user questions. • Authored model training data to improve LLMs. • Edited and reviewed AI outputs for quality control. • Evaluated and stress-tested model instruction sensitivity.

2025 - 2025

Data Labeler / AI Annotation Specialist

OtherTextClassification

At VoxMind AI, I labeled and validated large-scale text and multimedia datasets for AI training and evaluation. I compared AI-generated outputs for factual, logical, and stylistic errors. I maintained detailed annotation consistency using taxonomies and benchmarks. • Handled repetitive, detail-intensive workflows. • Ensured annotation quality and reliability. • Surface subtle inconsistencies between outputs. • Supplied structured data for model evaluation pipelines.

At VoxMind AI, I labeled and validated large-scale text and multimedia datasets for AI training and evaluation. I compared AI-generated outputs for factual, logical, and stylistic errors. I maintained detailed annotation consistency using taxonomies and benchmarks. • Handled repetitive, detail-intensive workflows. • Ensured annotation quality and reliability. • Surface subtle inconsistencies between outputs. • Supplied structured data for model evaluation pipelines.

2023 - 2024

Content Reviewer & AI Response Evaluator

OtherText

As a Content Reviewer & AI Response Evaluator for Mindri AI, I assessed AI-generated responses against standards for quality and relevance. I annotated model strengths and weaknesses across varied topics. I maintained consistency and speed in a high-volume review environment. • Evaluated both text and video AI outputs. • Applied structured guidelines for annotation. • Ensured clarity, tone, and completeness in responses. • Provided improvement feedback for AI models.

As a Content Reviewer & AI Response Evaluator for Mindri AI, I assessed AI-generated responses against standards for quality and relevance. I annotated model strengths and weaknesses across varied topics. I maintained consistency and speed in a high-volume review environment. • Evaluated both text and video AI outputs. • Applied structured guidelines for annotation. • Ensured clarity, tone, and completeness in responses. • Provided improvement feedback for AI models.

2023 - 2024

AI Data Annotator (Healthcare Project)

OtherClassification

At Omdena Local Chapter, I labeled and validated medical imaging and clinical text data for AI healthcare projects. I delivered structured annotation supporting NLP and imaging model pipelines. I authored documentation to improve annotation workflow scalability. • Handled both medical imaging and text datasets. • Produced data for NLP and computer vision models. • Provided quality-checked labels for healthcare AI. • Documented annotation practices for future teams.

At Omdena Local Chapter, I labeled and validated medical imaging and clinical text data for AI healthcare projects. I delivered structured annotation supporting NLP and imaging model pipelines. I authored documentation to improve annotation workflow scalability. • Handled both medical imaging and text datasets. • Produced data for NLP and computer vision models. • Provided quality-checked labels for healthcare AI. • Documented annotation practices for future teams.

2022 - 2022

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Education

Work History