Julian Niedermeier
Solutions Architect at QuantumBlack, AI by McKinsey
Potsdam, Brandenburg, Germany
Summary
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Rockstar🎓
Top SchoolJulian Niedermeier is a Solutions Architect with 11 years of experience designing and scaling cloud-native, distributed systems across AWS, Azure, and GCP that power high-throughput platforms and billion-dollar payout workloads. He bridges product strategy and engineering, cutting time-to-value by 66% and cloud costs by 31% through pragmatic architecture, automation, and multi-tenant security practices. Julian combines a strong ML research background—contributing performance improvements to the widely-used UMAP library and publishing work on large-scale biomedical text search—with hands-on microservice and Kubernetes delivery. Based in Potsdam, he is as comfortable optimizing petabyte-scale databases as he is mentoring cross-functional teams and turning stakeholder complexity into reliable, performant systems.
11 years of coding experience
1 year of employment as a software developer
Master of Science (M.Sc.) IT Systems Engineering, Master of Science (M.Sc.) IT Systems Engineering at Hasso Plattner Institute
English, German, Spanish
Github Skills (14)
file-handling10
file-processing10
markdown10
machine-learning10
numba10
markdown-it10
file-access10
knn10
python10
fileio10
numpy10
visualizations9
image-processing9
visualization9
Programming languages (16)
Github contributions (5)
lmcinnes/umap
Aug 2019 - Apr 2020
Uniform Manifold Approximation and Projection
Role in this project:
ML Engineer
ML EngineerContributions:17 commits, 11 PRs, 7 pushes in 7 months
Contributions summary:Julian contributed significantly to the optimization and maintenance of the `umap` library. They implemented a fast k-NN indices calculation using `numba` for performance enhancement. They also improved code formatting and structure, refactoring the code to use `knn_indices.size` for calculations. Additionally, the user updated the documentation to include animated HTML5 videos, suggesting improvements to the user experience.
projectiondimensionality-reductionmachine-learningtopological-data-analysisapproximation
ssine/pptx2md
Oct 2020 - Oct 2020
a pptx to markdown converter
Role in this project:Backend Developer
Backend DeveloperContributions:6 commits, 2 PRs, 2 comments in 2 days
Contributions summary:Julian primarily focused on improving the `pptx2md` converter's functionality and robustness. Their contributions included adding crucial `flush` and `close` methods to the outputter and parser to ensure proper output when used as a library. They also implemented proper path handling for image exports and fixed an image processing issue.
markdown-convertertable-of-contentspptxto-markdownmarkdown
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