Willi Gierke
Software Engineer at Google
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolWilli Gierke is a software engineer with 12 years of experience, currently building systems at Google in Zurich. He combines production engineering at a top-tier tech company with hands-on contributions to open-source ML tooling—most notably improving parallel image download pipelines in the cleverhans adversarial example library. His background spans full-stack and backend work, from adding DICOM inspection and Git-version UI features in a medical challenge frontend to real-time anomaly detection research during his time at Hasso Plattner Institute. Comfortable across Python, web stacks, and distributed processing, he brings both research rigor and pragmatic engineering to production problems. Colleagues describe him as someone who improves developer experience as readily as runtime efficiency, quietly surfacing useful tooling and automation.
12 years of coding experience
3 years of employment as a software developer
Bachelor of Science (B.Sc.), IT-Systems Engineering, Bachelor of Science (B.Sc.), IT-Systems Engineering at Hasso Plattner Institute
English, German, French, Latin
Github Skills (22)
python10
django10
python-multiprocessing10
multi-process10
multiprocessing10
image-processing9
benchmark9
benchmarking9
front-end-development9
html8
machine-learning8
css8
restful-api7
api-design7
api-rest7
Programming languages (16)
Github contributions (5)
drivendataorg/concept-to-clinic
Aug 2017 - Dec 2019
ALCF Concept to Clinic Challenge
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:46 commits, 44 PRs, 218 comments in 2 years 4 months
Contributions summary:Willi contributed to the project by adding Sphinx autodoc for documentation generation, improving the project's maintainability and developer experience. They implemented a feature to display the current Git version in the top-level navigation of the frontend, enhancing user information. The user also added functionality to inspect DICOM directories and create model instances, integrating backend image processing capabilities.
clinic
cleverhans-lab/cleverhans
Jul 2017 - Sep 2017
An adversarial example library for constructing attacks, building defenses, and benchmarking both
Role in this project:ML Engineer
ML EngineerContributions:5 commits, 1 PR, 4 comments in 1 month
Contributions summary:Willi contributed to the image downloading functionality within the adversarial example library. Their work involved modifying the existing image download script to use multithreading, improving efficiency. Further contributions include reverting the multithreaded implementation and adding a new, multiprocessed version. Finally, they consolidated the parallel capabilities into the main download_images script, including the ability to specify the number of threads to use.
benchmarkingrobustnessadversarial-machine-learningsecurityadversarial
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.