Nahom Tsehaye

I’m a civil engineering graduate focused on turning complex visual models and quantitative datasets into clean, well-labeled, high-fidelity inputs for AI. I bring an analytical, detail-first mindset that emphasizes pattern identification, rigorous quality control, and precise documentation.

In my civil engineering internship, I processed and verified high-precision structural blueprints and technical datasets using AutoCAD. I systematically reviewed and audited drawings to cross-reference information, flag annotation errors, and maintain data integrity across active documentation streams.

To support AI and data workflows, I specialize in visual and textual labeling, categorization, object tracking, and error detection. I also apply structured organization, systematic categorization, and problem-solving to ensure datasets are consistent, validated, and ready for evaluation and annotation pipelines.

Alongside technical work, I’ve managed real-time priorities in service operations, strengthening my responsiveness and clarity of communication. I’m excited to contribute to content annotation and data evaluation workflows that demand strict accuracy, clear standards, and continuous improvement.