Jiří Šimša
Senior Staff Software Engineer at Google DeepMind
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolJiří Šimša is a Senior Staff Software Engineer based in Zurich with 13 years of experience designing and shipping distributed systems and ML infrastructure. He has driven cross-organizational engineering at Google and DeepMind, leading large teams and owning release configuration and pipelines for Gemini products that cut end-to-end release-cycle time from days to hours. His hands-on background includes co-developing tf.data at Google and contributing to prominent open-source projects like TensorFlow and Alluxio, improving data pipelines, symbolic checkpointing, and UFS-related deployment code. Jiří combines deep academic training (PhD in Computer Science from Carnegie Mellon) with product-focused delivery, routinely taking projects from core implementation to production rollouts. He prefers roles that blend technical leadership with AI/ML innovation and has a track record of scaling complex systems and operationalizing cutting-edge models. A less obvious strength is his emphasis on release reliability and orchestration—optimizing pipelines and configs to make ambitious launches predictable and fast.
13 years of coding experience
11 years of employment as a software developer
M.S., Computer Science, M.S., Computer Science at Masarykova univerzitaPh.D., Computer Science, Ph.D., Computer Science at Carnegie Mellon University
English, Czech
Stackoverflow
315reputation
31kreached
11answers
1question
Github Skills (23)
filesystem10
checkpoint10
data-pipelines10
python10
scripting10
machine-learning10
java10
checkpointing10
javas10
deeplearning-ai10
script10
deep-learning10
tensorflow10
sh10
shell10
Programming languages (7)
Github contributions (5)
Alluxio/alluxio
Aug 2015 - Jul 2017
Alluxio, data orchestration for analytics and machine learning in the cloud
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1655 commits, 589 PRs, 397 pushes in 1 year 10 months
Contributions summary:Jiří's contributions primarily focused on improvements and changes within the Alluxio deployment module, specifically updating and modifying related functionalities. This included changes to shell scripts and Java classes that are related to file system operations. The commits involved merging updates and introducing changes in UFS-related functionalities.
data-analysisvirtual-distributed-filesystemanalyticsorchestrationdata-science
tensorflow/tensorflow
Jul 2017 - Dec 2022
An Open Source Machine Learning Framework for Everyone
Role in this project:ML Engineer
ML EngineerContributions:199 reviews, 679 commits, 14 PRs in 5 years 6 months
Contributions summary:Jiří's contributions primarily focused on enhancements to the TensorFlow data pipeline, specifically the `tf.data` module. They implemented an index-based shuffling utility and added support for symbolic checkpointing within the TFRecordDataset. Further work included updates to improve symbolic checkpointing by supporting "name + key" versions of read/write methods, alongside making `shuffle` and `parallel_batch` compatible with symbolic checkpointing.
pythondata-sciencedeep-learningmlmachine-learning
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