Daniel González is an AI architect and project lead based in Vienna with eight years of experience turning research-grade expertise into production AI and data platforms. With a PhD-trained background in renewable-energy materials and academia-to-industry experience at institutions like TUM and Berkeley Lab, he blends rigorous experimental thinking with practical software and ML engineering. At paiqo he designs scalable, secure AI architectures and leads cross-functional delivery of both classical and generative AI initiatives, often acting as the primary technical client contact and proposal contributor. His career spans energy systems, semiconductor physics, aviation-tech, and renewables, giving him a rare systems-level perspective on applying AI to physical and operational domains. Results-oriented and methodical, he focuses on clean, testable solutions and aligning AI roadmaps with measurable business outcomes. An understated strength is his ability to translate complex scientific concepts into pragmatic product features that drive adoption and long-term partnerships.
7 years of coding experience
8 years of employment as a software developer
PhD (Physics) / Dr. rer. nat., Renewable energies. Material sicence, PhD (Physics) / Dr. rer. nat., Renewable energies. Material sicence at Technical University Munich
Diplomarbeit / Diplom thesis, Renewable energies, Physics, Material Science, Diplomarbeit / Diplom thesis, Renewable energies, Physics, Material Science at Technische Universität München
Dipl.Phys. / Llicenciat, Physics, Dipl.Phys. / Llicenciat, Physics at Universitat de Barcelona
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Daniel González - AI Architect & Project Lead at paiqo