Iwuji Franklin

Evaluated AI-generated responses for factual accuracy, instruction adherence, clarity, and safety compliance, improving model trustworthiness and reliability. Performed prompt engineering and optimization tasks to enhance model performance and response quality. Reviewed large datasets and annotations used in machine learning training pipelines to maintain data integrity for robust model development. Collaborated remotely with AI teams to refine evaluation guidelines and ensure consistent content quality across diverse AI applications. Conducted structured QA checks using rubrics and benchmarking standards to maintain high content quality.

Supported infrastructure stability through proactive system monitoring and troubleshooting to minimize downtime and ensure continuous service availability. Assisted with deployment and maintenance of server environments, contributing to smooth application delivery. Gained hands-on experience with system monitoring, diagnostics, and collaborative IT operations, along with practical documentation skills to improve team efficiency.

Built robust backend solutions and optimized data pipelines to support real-time monitoring and improve engineering operational efficiency. Developed backend services that powered real-time dashboards and monitoring systems, enhancing operational visibility and decision-making. Automated reporting workflows to reduce manual effort and increase data accuracy. Enhanced scientific data visualization tools for materials testing and analysis, providing clearer insights for R&D teams.