Mason Kramer
Senior Software Engineer at Sadhana Software LLC
Mountain View, California, United States
Summary
👤
Senior🎓
Top SchoolMason Kramer is a Senior Software Engineer in Mountain View with 13 years of experience building high-performance systems across healthcare, seismic imaging, and search. Currently at Google and formerly Head of Search/VP of Engineering at freespoke.com, he focuses on making search features faster to render and easier to build while shipping robust backend systems. His work spans application and systems programming, from EHR and medical billing platforms to HPC seismic voxel processing and radiology informatics. An active open-source contributor, he implemented TFRecord read/write support and CRC32-backed integrity in the tensorflow/rust bindings, showing attention to data integrity and low-level performance. Mason also ships consumer-facing software—he’s the sole author of Synchronaut, a long-lived iPhone sound synthesizer—demonstrating both product sensibility and deep implementation skill.
13 years of coding experience
7 years of employment as a software developer
Bachelor of Arts (B.A.), History, Bachelor of Arts (B.A.), History at Goucher CollegePostbac Premedical certificate, Cell/Cellular and Molecular Biology, 3.8, Postbac Premedical certificate, Cell/Cellular and Molecular Biology, 3.8 at Brandeis University
Stackoverflow
9,440reputation
646kreached
79answers
48questions
git
top-5%
version-control
top-5%
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top-1%
Github Skills (19)
machine-learning10
websocket10
io10
tensorflow10
rust10
git9
version-control9
data-structures8
data-structure8
algorithms8
algorithm8
server-side-javascript6
nodejs6
git-svn6
http6
Programming languages (14)
Github contributions (5)
tensorflow/rust
May 2018 - Mar 2020
Rust language bindings for TensorFlow
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 commits, 2 PRs, 27 comments in 1 year 9 months
Contributions summary:Mason primarily focused on implementing and refining the TFRecord writing and reading functionalities within the Rust bindings for TensorFlow. They introduced a `RecordWriter` and `RecordReader` struct, enabling the creation and parsing of TFRecord files. The contributions involved incorporating CRC32 checksums for data integrity and utilizing stack allocation for performance. These changes demonstrate expertise in handling the TFRecord format, essential for efficient data storage and retrieval in machine learning pipelines.
rust-languagetensorflowrustmachine-learning
masonk/rust
May 2018 - Mar 2020
Rust language bindings for TensorFlow
Contributions:12 pushes in 1 year 9 months
rustrust-languagetensorflowlanguage-bindings
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