Ryan Kuester is a Principal Embedded Linux Engineer with 16 years of hands-on experience building and optimizing software for resource-constrained devices from his base in Chicago. He leads embedded Linux initiatives at Insymbols, combining deep low-level systems expertise with practical product delivery. An active contributor to TensorFlow Lite Micro, Ryan has helped port and optimize core ML operators—like SPACE_TO_DEPTH—demonstrating a specialty in bringing machine learning inference to microcontrollers. Colleagues rely on him to bridge firmware, kernel, and ML inference stacks, and he has a track record of improving test infrastructure to make embedded deployments more reliable.
Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).
Role in this project:
ML Engineer
Contributions:34 reviews, 7 commits, 106 PRs in 1 year 7 months
Contributions summary:Ryan contributed to the implementation and porting of the SPACE_TO_DEPTH operator, a core component for machine learning model deployment on resource-constrained embedded targets. Their work involved syncing reference implementations, removing lite-specific code, and integrating the operator into the micro framework, along with corresponding unit tests. The user's commits show a focus on adapting and optimizing TensorFlow Lite operations for microcontrollers, as well as adding testing. The user also made contributions that improved the test setup of the project.
Contributions:4 commits, 1 push, 1 tag in 5 years 6 months
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Ryan Kuester - Principal Embedded Linux Engineer at Insymbols