Summary
Daniel Wessel is a Machine Learning Specialist and AI Cluster Lead based in Munich with a decade of experience building production ML systems across automotive, industrial inspection, energy forecasting, and telecom research. He leads an AI hub at Motius, supervising engineers, supporting sales and hiring, and delivering projects from in-car voice assistants and real-time object detection to federated learning and self-supervised approaches for low-label regimes. His technical breadth spans CNNs and Transformers for imaging and ultrasonic analysis, NLP pipelines for document classification and translation-quality metrics, and forecasting systems for electricity grids. He has a strong academic foundation with a Master’s in Informatics from TUM and hands-on product experience dating back to early cloud and frontend work at global firms and startups. Colleagues rely on him for turning research ideas—like agentic workflows and Beyond-5G AI applications—into deployable prototypes that address real operational constraints. He combines research-minded experimentation with practical delivery, often tackling problems where labeled data is scarce.
10 years of coding experience
1 year of employment as a software developer
California Polytechnic State University, San Luis Obispo
Master’s Degree, Informatics, 1.3, Master’s Degree, Informatics, 1.3 at Technical University Munich
Spanish, English, German