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Youssef is a Computer Vision and Machine Learning engineer focused on building reliable AI systems that deliver measurable results. His work spans real-time defect detection, high-throughput CV pipelines, and AI workflow automation.

At AiCENTIVE, he owned the end-to-end development of a tax email automation solution, taking it from concept to MVP. The system ingests Gmail and Microsoft 365 mailboxes, summarizes emails and attachments, extracts structured tasks, and produces DATEV-ready exports for accounting workflows.

Before that, Youssef worked at CarboScreen, where he designed and deployed a real-time defect detection system for carbon-fiber manufacturing. He optimized inference with ONNX and TensorRT, achieving throughput above 10k images per second, and supported deployment on RTX and NVIDIA Jetson platforms.

His technical projects include a two-stage textile inspection pipeline with YOLOv8 and MobileNet, edge deployments with sub-millisecond inference latency, and a Graph-RAG assistant combining knowledge graphs with LLMs.

Youssef earned his B.Sc. in Computer Science and Engineering at the German International University in Berlin and completed an exchange semester at RWTH Aachen University. His thesis focused on computer vision for textile manufacturing quality control.

As CTO, he leads AI systems engineering across product, deployment, and research, with a focus on reliable automation, scalable infrastructure, and pragmatic delivery.