Summary
Martin Ueding is a Staff Research High Performance Computing Engineer at DeepL with 15 years of experience bridging computational physics, numerical methods, and machine learning for NLP. He holds a PhD in computational/theoretical physics and has a strong track record building performant C++, Python, and R software for large-scale numerical problems and neural machine translation. At DeepL he progressed from research scientist to staff engineer, applying HPC techniques to accelerate model training and inference. His background in lattice scattering and administering research compute clusters gives him uncommon depth in both algorithmic theory and practical system operations. He also tutors and mentors regularly, translating complex numerical concepts into teachable code and tools. Based in Bonn, he combines academic rigor with production-grade engineering to deliver efficient, reproducible ML systems.
15 years of coding experience
10 years of employment as a software developer
PhD (estimated for October 2020), Physics, Magna Cum Laude, PhD (estimated for October 2020), Physics, Magna Cum Laude at Rheinische Friedrich-Wilhelms-Universität Bonn
English, German