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Mutiyat Alimi

Data Annotator, Multimodal Evaluation

Nigeria flagLagos, Nigeria
$10.00/hrIntermediateOther

Key Skills

Software

Other

Top Subject Matter

Multimodal AI/LLM outputs
Conversational AI/Persona alignment
Content Moderation

Top Data Types

TextText
ImageImage
DocumentDocument

Top Task Types

ClassificationClassification

Freelancer Overview

Data Annotator, Multimodal Evaluation. Core strengths include Other. Education includes Bachelor of Science, University of Unilorin (2019). AI-training focus includes data types such as Text and Image and labeling workflows including Evaluation, Rating, and Classification.

IntermediateEnglish

Labeling Experience

Image Annotator, Text-to-Image Alignment

OtherImage
Participated in the Text-to-Image Alignment project, evaluating AI-generated images for accurate alignment with given text prompts. Checked images for adherence to specific instructions and prompt descriptions and provided structured annotations. Ensured a high-quality labeled dataset was produced to improve AI's text-to-image generation capabilities. • Reviewed and annotated AI-generated images for correctness. • Evaluated fidelity to prompts and instruction guidelines. • Provided detailed feedback for model improvement. • Supported training data creation for generative models.

Participated in the Text-to-Image Alignment project, evaluating AI-generated images for accurate alignment with given text prompts. Checked images for adherence to specific instructions and prompt descriptions and provided structured annotations. Ensured a high-quality labeled dataset was produced to improve AI's text-to-image generation capabilities. • Reviewed and annotated AI-generated images for correctness. • Evaluated fidelity to prompts and instruction guidelines. • Provided detailed feedback for model improvement. • Supported training data creation for generative models.

Present

Content Moderator & Data Annotator, Disagreement & Safety

OtherTextClassification
Contributed to the People Disagree-Content Moderation and Safety Annotation Project, focusing on classifying social media content. Classified posts based on intent, sentiment, and sensitivity and moderated teen-centric platforms. Annotated nuanced disagreements to enhance model understanding of conflicting viewpoints. • Identified harmful or policy-violating content. • Applied content moderation guidelines on sensitive material. • Labeled intent, sentiment, and disagreement in text. • Supported safety and moderation improvements for AI.

Contributed to the People Disagree-Content Moderation and Safety Annotation Project, focusing on classifying social media content. Classified posts based on intent, sentiment, and sensitivity and moderated teen-centric platforms. Annotated nuanced disagreements to enhance model understanding of conflicting viewpoints. • Identified harmful or policy-violating content. • Applied content moderation guidelines on sensitive material. • Labeled intent, sentiment, and disagreement in text. • Supported safety and moderation improvements for AI.

Present

Data Annotator, Static Preference Annotation

OtherText
Participated in the Static Preference Annotation Project by analyzing user-AI conversations. Selected and annotated preferred responses based on clarity, tone, and persona alignment to improve conversational AI models. Flagged unsafe or inconsistent responses and contributed to training more effective AI personas. • Annotated response quality to train AI preferences. • Evaluated alignment with clarity, tone, and persona requirements. • Labeled unsafe or policy-violating responses. • Ensured improved AI conversational alignment via annotation.

Participated in the Static Preference Annotation Project by analyzing user-AI conversations. Selected and annotated preferred responses based on clarity, tone, and persona alignment to improve conversational AI models. Flagged unsafe or inconsistent responses and contributed to training more effective AI personas. • Annotated response quality to train AI preferences. • Evaluated alignment with clarity, tone, and persona requirements. • Labeled unsafe or policy-violating responses. • Ensured improved AI conversational alignment via annotation.

Present

Data Annotator, Multimodal Evaluation

OtherText
Worked on MMMLM-Multimodal Evaluation for Large Language Models, evaluating AI outputs across text, images, audio, and video. Compared multiple model responses and selected the most accurate or appropriate output as part of model enhancement. Provided structured feedback to guide error and bias reduction in multimodal AI systems. • Assessed model performance in different content types. • Flagged errors, inconsistencies, and potential bias. • Applied strict annotation guidelines and quality standards. • Evaluated and rated AI-generated outputs for feedback-driven model improvements.

Worked on MMMLM-Multimodal Evaluation for Large Language Models, evaluating AI outputs across text, images, audio, and video. Compared multiple model responses and selected the most accurate or appropriate output as part of model enhancement. Provided structured feedback to guide error and bias reduction in multimodal AI systems. • Assessed model performance in different content types. • Flagged errors, inconsistencies, and potential bias. • Applied strict annotation guidelines and quality standards. • Evaluated and rated AI-generated outputs for feedback-driven model improvements.

Present

Education

U

University of Unilorin

Bachelor of Science, Chemistry

Bachelor of Science
2015 - 2019

Work History

H

HUGO

DATA ANNOTATOR

LAGOS
2025 - 2026