Dan Graur is a Senior Research Engineer at Google DeepMind with a decade of experience building large-scale ML systems and a PhD in Computer Science from ETH Zurich. He has been a core contributor to Gemini Multimodality and previously tackled input bottlenecks and predictive indexing during multiple research internships at Google. His background spans systems, distributed data pipelines, and ML framework work—from tf.data and Flax to production research—reflecting a blend of research rigor and production impact. Dan’s academic work produced novel methods in multiple instance learning and he has a history of cross-institutional collaboration (ETH, TU Delft, Technical University of Cluj Napoca) that underpins his ability to bridge theory and engineering. Notably, he moved from doctoral research into influential roles on cutting-edge multimodal models, demonstrating both deep technical depth and product-oriented delivery.
10 years of coding experience
8 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at ETH Zurich & TU Delft
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Technical University of Cluj Napoca
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at ETH Zürich
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Dan Graur - Senior Research Engineer at Google DeepMind