Fabian Joswig
Staff Research Engineer at DeepL
Cologne, North Rhine-Westphalia, Germany
Summary
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Rockstar🎓
Top SchoolFabian Joswig is a Staff Research Engineer at DeepL with nine years of experience bridging theoretical physics and large-scale machine learning, currently focused on building and optimizing multimodal LLMs. He holds a summa cum laude PhD in Theoretical and Computational Particle Physics and transitioned from postdoctoral research on quantum field theory and high-performance computing to applied deep learning at DeepL. Fabian combines rigorous mathematical foundations with production ML engineering, contributing open-source tools like pyerrors and autograd that reflect his emphasis on reproducible, differentiable tooling. Based in Cologne, he excels at turning research-grade models into scalable systems and brings a rare blend of academic depth and pragmatic software craftsmanship to multilingual and multimodal AI challenges.
9 years of coding experience
7 years of employment as a software developer
Dr. rer. nat. (PhD), Theoretical and Computational Particle Physics, Summa cum laude, Dr. rer. nat. (PhD), Theoretical and Computational Particle Physics, Summa cum laude at University of MünsterBachelor of Science - B.Sc., Physics, Bachelor of Science - B.Sc., Physics at Technological University Dublin
German, English
Github Skills (70)
lattice10
python10
autocorrelation10
mathematical10
transformer-models10
correlation10
gtk10
floating10
serverless10
monte-carlo10
markov-chain10
particle-physics10
simulations10
avx10
github-bot10
Programming languages (4)
Github contributions (5)
fjosw/Hadrons
Apr 2021 - Dec 2024
Grid-based workflow management system for lattice field theory simulations
Contributions:110 pushes, 26 branches in 3 years 8 months
management-systemworkflow-basedworkflow-management-systemlatticesimulations
fjosw/ADjson.jl
Feb 2022 - Jul 2023
ADerrors.jl input routines for the json.gz format used within pyerrors
Contributions:3 releases, 1 PR, 30 pushes in 1 year 4 months
jsonroutinesjulia
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