Finn Gaida
CTO @Nomaze
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WORK HISTORY
CTO @Nomaze
Munich, DE
NoMaze is building the AI decision engine for modern plant breeding.Breeding programs operate on increasingly complex genomic, phenotypic and environmental datasets, yet most prediction workflows remain fragmented and computationally constrained. We design and deploy production-grade machine learning infrastructure that transforms heterogeneous biological data into scalable, high-confidence genetic predictions.As CTO, I define and execute the company’s technical vision. This includes: • Architecting the core ML systems that power our predictive models • Designing data pipelines capable of handling high-dimensional genomic and field trial data • Building scalable cloud-native infrastructure for model training and deployment • Establishing engineering standards for reliability, performance and reproducibility • Hiring and leading the engineering teamOur focus is not experimental AI. We build robust, enterprise-ready systems designed to operate inside real breeding environments. The ambition is to establish NoMaze as the technical backbone for data-driven crop development globally.
EDUCATION
University of Groningen
Semester abroad, Artificial Intelligence
Technical University of Munich
Bachelor of Science (B.Sc.), Informatik
Alstergymnasium Henstedt-Ulzburg
Abitur, Physics
Technical University of Munich
Master of Science - MS, Informatik
SKILLS
ABOUT FINN GAIDA
As CTO & Co-Founder of NoMaze, I lead the technical architecture and long-term technology strategy behind our AI platform for plant breeding.Modern breeding programs generate vast genomic, phenotypic and environmental datasets, yet decision-making tools remain fragmented and difficult to scale. At NoMaze, we are building robust machine learning systems that transform complex biological data into reliable, operational predictions embedded directly into breeding workflows.My role spans technical vision, system architecture, model development and engineering team leadership. I focus on building scalable, production-ready ML infrastructure that meets the reliability and performance standards of enterprise breeding organizations.My background is in computer science and intelligent systems, with a strong focus on machine learning and data-driven modeling in complex environments. I am motivated by building durable systems that turn advanced algorithms into practical tools used in real-world decision processes.At NoMaze, my objective is to design and scale the technical foundation that enables the next generation of data-driven crop development.
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