Tim Wedde
Software Engineer at Boosting Alpha B.V.
Grefrath, North Rhine-Westphalia, Germany
Summary
👤
Senior🎓
Top SchoolTim Wedde is a software engineer with 9 years of experience specializing in machine learning, DevOps, Google Cloud Platform and Linux system administration, based in Grefrath, Germany. He consistently brings pragmatic, production-first thinking to backend systems—evidenced by contributions to the Litestar ASGI framework improving OpenAPI schema generation and error handling. Tim has held engineering and quantitative roles across startups and research-adjacent teams (AgroWizard, Verdify, Boosting Alpha, Genzai), blending data-focused analytics with robust infrastructure skills. He prefers practical, lightweight solutions—“building solutions for odd problems you didn't know you had”—and explicitly avoids Java roles, reflecting a clear toolset and cultural fit.
9 years of coding experience
Bachelor of Science - BS Software Engineering, Bachelor of Science - BS Software Engineering at Fontys Venlo University of Applied Sciences
English, German
Github Skills (9)
python10
openapi10
testing10
asgi9
api9
pydantic8
asyncio7
redoc6
swagger6
Programming languages (7)
Github contributions (5)
litestar-org/litestar
May 2022 - Jun 2022
Production-ready, Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant APIs
Role in this project:
Backend Developer
Backend DeveloperContributions:1 review, 7 commits, 4 PRs in 23 days
Contributions summary:Tim primarily focused on enhancing the OpenAPI schema generation and error handling within the Litestar framework. They addressed dependencies in schema generation, removed redundant code, and added tests. Further, the user conformed exceptions to the existing OpenAPI schema and updated tests to account for the changes. They also modified the typing of the `extra` field in error responses.
api-clientapiasgipythonredoc
timwedde/composer
Feb 2018 - Feb 2021
Generating music with Machine Learning
Contributions:68 commits, 8 PRs, 23 pushes in 3 years
musicpythonmachine-learning
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