Bryan Cutler
Software Engineer at IBM
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolBryan Cutler is a seasoned software engineer with 11 years of professional experience and a decade-long track record at IBM designing backend systems for big data and analytics. He combines strong mathematical foundations and an MS in Computer Science to build machine learning, computer vision, and data-processing pipelines, from embedded sensor software to large-scale distributed query engines. An active open-source contributor, Bryan has improved core data tooling in projects like Apache Arrow, Spark, Presto, and TensorFlow I/O—work that touches high-performance Arrow-Pandas integrations and Velox plan conversion for SQL engines. He brings hands-on systems expertise spanning C++/Python backend development, zero-copy data paths, and practical algorithm tuning for real-world sensing systems. Based in San Jose, he pairs product-focused engineering with academic rigor and a history of turning research ideas into production-ready software.
11 years of coding experience
11 years of employment as a software developer
Bachelor of Science (B.S.), Computer Engineering, Bachelor of Science (B.S.), Computer Engineering at University of California, Irvine
Github Skills (49)
apache-spark10
sql-query10
docker10
c-language10
spark10
python10
back-end-development10
data-set10
data-engineering10
dataframes10
pandas10
big-data10
arrow-keys10
dockers10
java10
Programming languages (9)
Github contributions (5)
apache/arrow
Nov 2016 - Mar 2022
Apache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:62 reviews, 90 commits, 172 PRs in 5 years 5 months
Contributions summary:Bryan primarily contributed to the Apache Arrow project by implementing and enhancing features related to the Python implementation, particularly within the pyarrow library. This included adding functionality such as `Schema.equals` and supporting the conversion of RecordBatches to Pandas DataFrames. They also made significant contributions to the Java component, supporting new metadata formats, and fixing issues related to JSON handling and data conversion. Further contributions included cleaning up the codebase by removing deprecated elements, fixing typos, and improving unit tests.
apache-arrowarrowparquet
tensorflow/io
Dec 2018 - Mar 2020
Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO
Role in this project:Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:1 release, 4 reviews, 47 commits in 1 year 3 months
Contributions summary:Bryan primarily contributed to the development of Arrow datasets and related functionalities within the TensorFlow I/O library. They implemented and refined operations for reading Arrow record batches from memory, Feather files, and streams, including support for batching, data type checking, and various batch modes. The user also integrated zero-copy mechanisms for efficient data transfer and enhanced the library's capabilities by adding support for boolean types and creating utilities for interfacing with Pandas DataFrames and Unix Domain Sockets. These contributions focused on improving data ingestion and processing pipelines for TensorFlow applications.
filesystemtensorflowtensorflow-iodatasetstreaming
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