Morounfoluwa I.

Key Skills

Software

Micro1

Top Subject Matter

NLP (Sentiment, Intent, NER) and LLM evaluation

Computer vision annotation for object detection

Video annotation for AI training

Top Data Types

Text

Image

Document

Top Task Types

Entity (NER) Classification

Object Detection

Action Recognition

Transcription

Bounding Box

Classification

Freelancer Overview

AI Data Annotation Specialist / Data Annotation (Multimodal & NLP). Core strengths include Micro1. Education includes Master of Arts, Nottingham Trent University. AI-training focus includes data types such as Text and Image and labeling workflows including Entity (NER) Classification, Object Detection, and Action Recognition.

Labeling Experience

DATA ANNOTATION•

ImageBounding BoxObject Detection

No description provided.

2023 - Present

AI Data Annotation Specialist / Data Annotation

Micro1ImageObject DetectionAction Recognition

Labeled and evaluated image content for AI training while adhering to bounding and annotation rules defined by the project. Conducted quality assurance reviews to catch annotation errors and ensure dataset reliability. Consistently maintained high accuracy standards and guideline compliance in remote work settings. • Performed image annotation for object detection use cases. • Followed detailed annotation guidelines to maintain consistency across projects. • Identified and corrected inconsistencies and edge cases during QA. • Met productivity targets and deadlines while sustaining 98%+ accuracy.

2023 - Present

AI Data Annotation Specialist / Data Annotation (Multimodal & NLP)

Micro1TextEntity (NER) Classification

Annotated and evaluated text datasets used to train machine learning and large language models, following detailed project guidelines. Reviewed AI-generated responses for accuracy, relevance, clarity, and overall user experience. Performed quality assurance checks by identifying annotation errors, inconsistencies, and edge cases to maintain high accuracy. • Conducted NLP tasks including sentiment, intent, and NER labeling. • Applied prompt-response ranking and comparative evaluation to improve model performance. • Ensured consistency and data integrity across annotation projects. • Maintained annotation accuracy rates above 98% while meeting productivity targets.

2023 - Present

Education

Work History