Sarah Lutteropp
Software Engineer, Site Reliability Engineering at Google
Augsburg, Bavaria, Germany
Summary
👤
Senior🎓
Top SchoolSarah Lutteropp is a software engineer and SRE at Google with 13 years of experience blending high-performance algorithm engineering and production reliability. She holds a PhD in Computer Science focused on phylogeny reconstruction, where she developed efficient heuristics and parallel implementations in C/C++/OpenMP/OpenMPI for NP-hard problems—work that informed contributions to bioinformatics tools like RAxML. At Google she supports dozens of internal services on-call, drives reliability improvements, and coaches engineers on designing robust systems. Her background spans research-grade algorithm development, end-to-end monitoring instrumentation at YouTube, and a curious maker streak in hardware and product design. Known for finding numerical and scalability edge cases, she combines deep theoretical insight with practical, production-grade optimizations.
13 years of coding experience
3 years of employment as a software developer
Abitur (Equivalent to A-levels), 1.1, Abitur (Equivalent to A-levels), 1.1 at Jacob-Grimm-Schule KasselBachelor of Science - BS, Computer Science, 2.3, Bachelor of Science - BS, Computer Science, 2.3 at Karlsruhe Institute of Technology (KIT)Gepr. ProduktdesignerIn (OfG), Industrial and Product Design, Gepr. ProduktdesignerIn (OfG), Industrial and Product Design at OfG / Online-Schule für Gestaltung
German, English, French, Ukrainian
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
algorithm10
c1710
data-structures10
bioinformatics10
algorithms10
c1110
data-structure10
binary-search9
Programming languages (5)
Github contributions (5)
stamatak/standard-RAxML
Mar 2016 - Apr 2016
Role in this project:
Back-end Developer / Algorithm Engineer
Back-end Developer / Algorithm EngineerContributions:6 commits, 3 PRs in 13 days
Contributions summary:Sarah significantly contributed to the implementation and optimization of a quartet sampling algorithm within the RAxML codebase. Their work involved modifying and adding new functions, including `sampleQuartetsWithoutReplacementA` and `sampleQuartetsWithoutReplacementD`, to improve the efficiency of quartet calculations. The user also addressed a numerical error, enabling the algorithm to handle larger datasets. Furthermore, they added extensive comments to improve code clarity.
lutteropp/raxml-ng
Apr 2019 - May 2021
RAxML Next Generation: faster, easier-to-use and more flexible
Contributions:192 commits, 175 pushes, 4 branches in 2 years 1 month
next-generationfasterflexible
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