Daniel Bevenius

Software Engineer at Hugging Face

Greater Stockholm Metropolitan Area Sweden
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Summary

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Rockstar
Daniel Bevenius is a seasoned software engineer with 17 years of experience, currently contributing to Hugging Face after a long tenure at Red Hat where he was a Principal Engineer and Node.js TSC member. He specializes in backend systems, runtime internals and build/tooling improvements, with deep contributions to Node.js core, libuv, OpenSSL and QUIC implementations. Equally comfortable in C/C++, Rust and Java, he has actively improved popular open-source ML and inference projects like whisper.cpp, llama.cpp and ggml, helping them build and compile reliably across CUDA/Metal targets. His work often targets subtle but high-impact areas—reducing duplication, suppressing compiler warnings, and hardening build processes—that improve maintainability across large codebases. Based in Stockholm, he combines systems-level craftsmanship with a pragmatic focus on developer experience and cross-platform stability.
code17 years of coding experience
job21 years of employment as a software developer
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Github Skills (101)

testing10
windows10
websocket10
c1110
c1710
javas10
mtls10
websockets-client10
code-cleanup10
embedded10
trace10
iot-devkit10
client-websocket10
slf4j10
code-optimization10

Programming languages (23)

JavaC++CSSJinjaRustCCMakeMakefile

Github contributions (5)

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ggml-org/whisper.cpp

Jan 2025 - Jul 2026

Port of OpenAI's Whisper model in C/C++
Role in this project:
userBack-end Developer
Contributions:122 reviews, 237 PRs, 152 pushes in 1 year 5 months
Contributions summary:Daniel primarily contributed to the internal workings of the whisper.cpp project, focusing on improving the underlying C/C++ code. Their work involved fixing typos, removing unnecessary code elements, and adjusting configurations. They also made modifications to the codebase related to CUDA and Metal to suppress compiler warnings and improve the build process.
cppopenaiwhisperspeech-to-texttransformer
ggml-org/ggml

Nov 2023 - May 2026

Tensor library for machine learning
Role in this project:
userBack-end Developer
Contributions:17 reviews, 41 PRs, 7 pushes in 2 years 6 months
Contributions summary:Daniel primarily contributed to code maintenance and bug fixes within the ggml library. Their work involved addressing typos in documentation, removing redundant includes and unnecessary macro calls, and suppressing compiler warnings. They also modified code related to the CUDA and Metal backends, addressing build issues. These contributions suggest a focus on improving code quality, fixing compiler warnings, and ensuring the library functions correctly across different platforms and build configurations.
machine-learningtensor
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