Okechukwu Nzekwe

Key Skills

Software

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Classification

Text Generation

Evaluation Rating

Computer Programming Coding

Freelancer Overview

I am a computer science professional with a PhD in Software Engineering, specializing in large language models, machine learning, and advanced data labeling systems. My experience includes designing and engineering scalable AI training workflows that integrate automated data labeling, rigorous quality checks, and dataset versioning, particularly for NLP and content analysis applications. I have implemented secure, real-time content labeling pipelines and contributed to frameworks that significantly reduce manual annotation efforts. My technical expertise covers Python, C++, TensorFlow, PyTorch, and cloud platforms such as AWS, Azure, and GCP, with a strong focus on dataset quality management, cybersecurity, and the development of robust, enterprise-grade AI solutions. I am passionate about advancing AI safety, reliability, and efficiency through innovative data annotation and model training practices.

Labeling Experience

AI Data Annotation & LLM Evaluation Specialist (Outlier AI Projects)

LabelboxTextClassificationText Generation

I contributed to large-scale AI training and evaluation projects focused on improving the performance, reasoning, and safety of large language models (LLMs). My responsibilities included: Performing Reinforcement Learning from Human Feedback (RLHF) evaluations Rating AI-generated responses based on accuracy, coherence, helpfulness, and safety Writing high-quality prompts and ideal responses for supervised fine-tuning (SFT) Identifying hallucinations, bias, and unsafe outputs during red teaming exercises Comparing multiple model outputs and selecting the most aligned response Applying structured rubrics and scoring guidelines to ensure consistency Providing detailed justification notes to support quality audits

I contributed to large-scale AI training and evaluation projects focused on improving the performance, reasoning, and safety of large language models (LLMs). My responsibilities included: Performing Reinforcement Learning from Human Feedback (RLHF) evaluations Rating AI-generated responses based on accuracy, coherence, helpfulness, and safety Writing high-quality prompts and ideal responses for supervised fine-tuning (SFT) Identifying hallucinations, bias, and unsafe outputs during red teaming exercises Comparing multiple model outputs and selecting the most aligned response Applying structured rubrics and scoring guidelines to ensure consistency Providing detailed justification notes to support quality audits

2022 - 2025

Education

Work History