Abidemi Rasheed

Key Skills

Software

Appen

Toloka

Remotasks

CVAT

Top Subject Matter

General AI/Conversational AI

AI Language Model/LLM

Computer Vision

Top Data Types

Text

Image

Document

Top Task Types

Classification

Freelancer Overview

Freelance AI Data Annotator & Evaluator. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Appen, Toloka, and Remotasks. Education includes Bachelor of Science, University of Ilorin (2016). AI-training focus includes data types such as Text and Image and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Freelance AI Data Annotator & Evaluator

AppenText

As a Freelance AI Data Annotator & Evaluator, I annotated and labeled large-scale datasets consisting of text, audio, and images to support supervised learning. My role focused on ranking and comparing AI-generated responses using detailed rubrics and providing structured rationales for labels. I ensured consistent, high-quality outputs while adhering to tight service level agreements and daily quotas. • Labeled large datasets to enhance supervised learning in multiple modalities. • Applied strict guideline interpretation for high-quality, reliable annotation outputs. • Provided clear, actionable feedback for prompt and response accuracy. • Identified ambiguities and edge cases to optimize annotation standards.

As a Freelance AI Data Annotator & Evaluator, I annotated and labeled large-scale datasets consisting of text, audio, and images to support supervised learning. My role focused on ranking and comparing AI-generated responses using detailed rubrics and providing structured rationales for labels. I ensured consistent, high-quality outputs while adhering to tight service level agreements and daily quotas. • Labeled large datasets to enhance supervised learning in multiple modalities. • Applied strict guideline interpretation for high-quality, reliable annotation outputs. • Provided clear, actionable feedback for prompt and response accuracy. • Identified ambiguities and edge cases to optimize annotation standards.

2025 - Present

AI Quality Assurance & Content Review Project

Text

I participated in quality assurance of AI-generated content by reviewing outputs for accuracy and compliance. My work involved identifying incorrect, biased, or low-quality responses to support iterative model improvement. I followed detailed quality guidelines and highlighted error patterns for further action. • Reviewed AI outputs across diverse content types for guideline compliance. • Identified hallucinations, bias, and inconsistencies in AI-generated text. • Provided actionable QA feedback to inform retraining cycles. • Supported cross-platform feedback loops to enhance AI system performance.

I participated in quality assurance of AI-generated content by reviewing outputs for accuracy and compliance. My work involved identifying incorrect, biased, or low-quality responses to support iterative model improvement. I followed detailed quality guidelines and highlighted error patterns for further action. • Reviewed AI outputs across diverse content types for guideline compliance. • Identified hallucinations, bias, and inconsistencies in AI-generated text. • Provided actionable QA feedback to inform retraining cycles. • Supported cross-platform feedback loops to enhance AI system performance.

2024 - Present

Data Annotation & Content Labeling Project

RemotasksImageClassification

In large-scale annotation projects, I performed multi-format data annotation including images and ensured rigorous quality control. Using various proprietary and crowd annotation platforms, I followed strict project guidelines for high inter-annotator agreement. I regularly flagged inconsistencies and improved overall dataset quality through structured review cycles. • Annotated image datasets to support computer vision model development. • Applied strict labeling standards and guidelines across multiple annotation tools. • Conducted reviews for annotation consistency and data quality. • Communicated edge cases and improved process documentation.

In large-scale annotation projects, I performed multi-format data annotation including images and ensured rigorous quality control. Using various proprietary and crowd annotation platforms, I followed strict project guidelines for high inter-annotator agreement. I regularly flagged inconsistencies and improved overall dataset quality through structured review cycles. • Annotated image datasets to support computer vision model development. • Applied strict labeling standards and guidelines across multiple annotation tools. • Conducted reviews for annotation consistency and data quality. • Communicated edge cases and improved process documentation.

2024 - Present

AI Response Evaluation & Ranking Project

TolokaText

On multiple projects, I evaluated AI-generated responses by assessing accuracy, relevance, and instruction compliance for quality improvement. My structured reasoning supported consistent dataset curation and model training. The process involved high-level review and feedback to optimize AI outputs and minimize errors. • Assessed AI response quality using detailed rubrics and feedback guidelines. • Ensured data consistency and reliability for training large language models. • Highlighted edge cases and response ambiguities for guideline improvement. • Contributed to iterative feedback and corrective dataset adjustments.

On multiple projects, I evaluated AI-generated responses by assessing accuracy, relevance, and instruction compliance for quality improvement. My structured reasoning supported consistent dataset curation and model training. The process involved high-level review and feedback to optimize AI outputs and minimize errors. • Assessed AI response quality using detailed rubrics and feedback guidelines. • Ensured data consistency and reliability for training large language models. • Highlighted edge cases and response ambiguities for guideline improvement. • Contributed to iterative feedback and corrective dataset adjustments.

2024 - Present

Education

Work History