Michael Ogbormeh

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Entity Ner Classification

Freelancer Overview

I am a detail-oriented IT specialist and software developer with hands-on experience supporting and securing complex systems, as well as designing and implementing web applications. My background includes developing and testing online platforms such as voting and search systems, where I ensured data integrity, security, and accuracy—skills directly transferable to data labeling and annotation roles. I am proficient in HTML, CSS, JavaScript, PHP, MySQL, and Laravel, and have experience working with AWS and cloud environments. My work has required close attention to data quality, robust documentation, and collaboration with multidisciplinary teams, making me well-equipped to contribute to AI training data projects across domains. I am passionate about using technology to solve real-world problems and am eager to apply my skills to support the development of high-quality AI systems.

Labeling Experience

LLM Training & Response Evaluation Project

Scale AITextEntity Ner Classification

Assisted in a large-scale LLM training and evaluation task with a focus on enhancing the overall performance of conversational AI models. This entailed annotating text data for intent detection, sentiment analysis, and named entity recognition (NER) categories. It also involved crafting high-quality prompt-response pairs for SFT. Assessed the relevance, accuracy, safety, tone, and overall compliance with specific guidelines of AI-generated text within the scope of RLHF. This task comprised labeling thousands of data points with stringent quality requirements, multiple levels of reviews, and constant calibration.

Assisted in a large-scale LLM training and evaluation task with a focus on enhancing the overall performance of conversational AI models. This entailed annotating text data for intent detection, sentiment analysis, and named entity recognition (NER) categories. It also involved crafting high-quality prompt-response pairs for SFT. Assessed the relevance, accuracy, safety, tone, and overall compliance with specific guidelines of AI-generated text within the scope of RLHF. This task comprised labeling thousands of data points with stringent quality requirements, multiple levels of reviews, and constant calibration.

2023 - 2024

Education

Work History