Martin Wicke
Director Principal Engineer at Google
San Francisco, California, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolMartin Wicke is a Director/Principal Engineer with over 15 years leading engineering teams and more than 25 years of hands-on software development across C++, Java, Python, JavaScript and Scala. He combines deep technical expertise in machine learning, VR/AR and high-performance computing with full-product lifecycle experience from prototype to launch, including founding a startup that applied ML/NLP to code education. At Google he has driven machine learning at scale and made notable open-source contributions to TensorFlow projects—models, docs, examples and TensorBoard—plus work on the XLA compiler for GPU optimization. His background spans academia, startups and large orgs, with numerous publications and patents reflecting a research-informed engineering approach. Known as a pragmatic technical leader and frequent speaker, he often bridges low-level systems work and developer-facing tooling to accelerate teams and products.
15 years of coding experience
9 years of employment as a software developer
Diplom Informatik, Diplom Informatik at RPTU Kaiserslautern-LandauDr. Sc. ETH Computer Graphics, Dr. Sc. ETH Computer Graphics at ETH Zürich
English, German, French
Stackoverflow
749reputation
15kreached
8answers
0questions
tensorflow
top-5%
Github Skills (34)
javascript10
c-language10
back-end-development10
python10
gpu-programming10
machine-learning10
ui-design10
uid10
tensorflow10
front-end-development10
xla10
compiler10
backend10
cprogramming-language10
documentation10
Programming languages (9)
Github contributions (5)
openxla/xla
Feb 2017 - Oct 2022
A machine learning compiler for GPUs, CPUs, and ML accelerators
Role in this project:
Backend Developer
Backend DeveloperContributions:22 commits in 5 years 9 months
Contributions summary:Martin's commits primarily involve modifications to the core XLA compiler codebase. These changes include refactoring code, merging changes, and addressing lint issues within the service and allocation tracker modules. The commits touch upon various aspects of the compiler's functionality, including argument validation, module configuration, and allocation tracking. A substantial amount of changes appear within `xla/service/gpu` suggesting involvement in GPU-specific compiler optimization and code generation.
compilercommunity-drivenmachine-learningmodular
tensorflow/docs
Jan 2016 - Mar 2021
TensorFlow documentation
Role in this project:Back-end Developer
Back-end DeveloperContributions:67 commits, 3 PRs, 3 branches in 5 years 2 months
Contributions summary:Martin primarily focused on modifying and updating files related to the TensorFlow documentation generator. Their work involved changes to the `gen_cc_md.py` and `gen_docs.sh` scripts, indicating a focus on improving the C++ documentation generation process. The user also merged branches and fixed documentation generation issues, ensuring the accuracy and completeness of the API documentation. They made updates to the `public_api.py` file, and the `parser.py` file, which are critical components of the documentation generation system.
deep-learningmachine-learningdeep-neural-networkstensorflow-tutorialstensorflow
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