Wisdom Aremu

Key Skills

Software

Clickworker

Top Subject Matter

No subject matter listed

Top Data Types

Image

Top Label Types

Relationship

Question Answering

Emotion Recognition

Object Detection

Freelancer Overview

I am an experienced AI Data Annotator, Evaluator, and Tester with a strong background supporting machine learning and large language model development for global remote-first companies. My expertise spans labeling and reviewing large-scale datasets across text, image, audio, and video modalities, with hands-on experience in both NLP and computer vision projects. I excel at evaluating AI-generated outputs for accuracy, relevance, and safety, as well as performing structured testing to identify model weaknesses and edge cases. I am highly skilled in executing high-volume microtasks, maintaining strict quality standards, and adhering to detailed annotation guidelines. My proficiency with platforms such as OpenTrain AI, various crowdsourcing tools, and web-based QA dashboards enables me to efficiently support the training and validation of advanced AI models, always ensuring data integrity and confidentiality.

Labeling Experience

Freelance Data Labeler / AI Data Annotator

ClickworkerImageRelationshipQuestion Answering

As a Freelance Data Labeler and AI Data Annotator, I labeled and validated large volumes of data for supervised and reinforcement machine learning. I executed high-precision microtasks across text, image, audio, and video datasets following strict annotation guidelines. My responsibilities included peer review, error detection, and adherence to quality and turnaround benchmarks. • Supported NLP and LLM system training via structured data labeling • Delivered labeled datasets for intent detection, sentiment tagging, and entity recognition • Applied annotation taxonomies for dataset consistency and conducted quality assurance checks • Used platforms such as OpenTrain and web annotation tools for scalable data processing

As a Freelance Data Labeler and AI Data Annotator, I labeled and validated large volumes of data for supervised and reinforcement machine learning. I executed high-precision microtasks across text, image, audio, and video datasets following strict annotation guidelines. My responsibilities included peer review, error detection, and adherence to quality and turnaround benchmarks. • Supported NLP and LLM system training via structured data labeling • Delivered labeled datasets for intent detection, sentiment tagging, and entity recognition • Applied annotation taxonomies for dataset consistency and conducted quality assurance checks • Used platforms such as OpenTrain and web annotation tools for scalable data processing

2023

Education

Work History