André Graubner

Principal Machine Learning Engineer at Topos Bio

United States
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Summary

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Senior
🎓
Top School
André Graubner is a Principal Machine Learning Engineer with eight years of experience building high-impact AI systems at the intersection of climate science, biotech, and foundational protein modeling. He led creation of the largest expert-labeled dataset for extreme weather and helped deliver the fastest AI-driven weather detector, and at NVIDIA improved probabilistic calibration of FourCastNet to near-IFS levels—work highlighted by Jensen Huang. Now at Topos Bio he focuses on foundation models for flexible proteins, bringing research rigor from academia (ETH Zürich, Tsinghua) and hands-on production experience across ESA, Berkeley Lab, and R&D roles. He combines strong Bayesian deep learning and dataset engineering skills with a knack for turning large, messy scientific problems into scalable AI solutions. An intriguing aside: his GitHub ethos—"types are rad"—hints at an engineer who values correctness and robust tooling as much as cutting-edge models.
code8 years of coding experience
job3 years of employment as a software developer
bookMaster of Science - MS Computer Science, Master of Science - MS Computer Science at Tsinghua University
bookBachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at ETH Zürich
languagesGerman, English, Chinese
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Github Skills (15)

simulator9
gaussian8
simulation8
optimization7
machine-learning6
python6
gaussian-processes6
hyperparameter-tuning4
analytics4
experimental-design4
posenet3
deep-neural-networks3
pose2
validation2
tensorflow1

Programming languages (2)

TypeScriptPython

Github contributions (5)

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andregraubner/ClimateNet

Nov 2020 - Oct 2021

Climate Analytics using Deep Neural Networks in Python.
Contributions:19 commits, 4 pushes, 9 comments in 11 months
analyticspythonclimateneural-networksmachine-learning
Contributions:17 pushes, 2 branches in 1 year 10 months
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André Graubner - Principal Machine Learning Engineer at Topos Bio