Juan Montenegro is a Senior Machine Learning Engineer based in Lausanne with a decade of experience building and deploying ML systems for medical imaging and multimodal clinical data. He holds a PhD in Machine Learning and has driven foundation-model development at Kaiko.ai, co-leading a pathology model trained on over 350 million tissue patches that achieved state-of-the-art results on pan-cancer and biomarker tasks. Juan pairs deep research experience—from a postdoc in MRI stroke prediction at Inselspital—with production engineering skills, having scaled distributed training across 64 H200 GPUs and authored an evaluation framework that became the open-source EVA library. He also secured €2.5M in translational research funding by proposing pipelines linking pixel-level spatial proteomics to tissue morphology, demonstrating an ability to translate technical advances into stakeholder value. Known for close collaboration with pathologists and computational biologists, he solves practical I/O and gigapixel image-processing bottlenecks while applying foundation models to improve health outcomes.
10 years of coding experience
6 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Universidad Nacional de Colombia
Doctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at University of Geneva
Post Doctoral Degree Educational/Instructional Technology, Post Doctoral Degree Educational/Instructional Technology at Medizinsammlung Inselspital Bern
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Juan Montenegro - Senior Machine Learning Engineer at kaiko.ai