Bryan Cutler - Software Engineer at IBM

Bryan Cutler

Software Engineer at IBM

San Jose, California, United States

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Summary

🤩

Rockstar

🎓

Top School

Bryan 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-engineering10

data-set10

dataframes10

pandas10

big-data10

arrow-keys10

dockers10

java10

Programming languages (8)

JavaC++ShellScalaGoHTMLJupyter NotebookPython

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

Contributions: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.

memorymulti-languagetoolboxacceleratedarrow

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

Contributions: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.

datasetstreamingsigextensionsfilesystem

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