Andrew Seidl is a Principal Engineer specializing in AI/ML infrastructure with 15 years of experience building high-performance, production-grade systems across cloud, GPU, and heterogeneous CPU environments. He has driven compute kernel development and platform rearchitectures—optimizing CUDA and CPU code, enabling GPU and CPU-only execution paths, and improving tiered storage for distributed analytics. At HEAVY.AI he combined hands-on C++/Go work with DevSecOps leadership to certify and deploy data platforms to AWS GovCloud, GCP, and Azure while standing up supply-chain and CI pipelines. His open-source contributions include build automation and CI improvements for the well-regarded Chrono physics engine and performance and import/security enhancements to HeavyDB, reflecting a long-standing focus on build systems and cross-platform portability. Based in Wisconsin, he pairs a rigorous mechanical engineering background with deep systems and DevOps instincts, often surfacing subtle build and platform issues that accelerate both development and deployment.
15 years of coding experience
14 years of employment as a software developer
Mechanical Engineering, Mechanical Engineering at University of Wisconsin-Madison
Maschinenbau (Mechanical Engineering), Maschinenbau (Mechanical Engineering) at Technische Hochschule Lübeck
Bachelor of Science (BS) Mechanical Engineering, Bachelor of Science (BS) Mechanical Engineering at Milwaukee School of Engineering
Contributions:1140 commits, 56 PRs, 517 pushes in 7 years 3 months
Contributions summary:Andrew primarily worked on optimizing and refactoring code for the heavyai/heavydb repository. They improved type checking with Boost libraries, added support for Google Test within the project structure, and integrated new functionalities related to data import, by adding features such as including custom s3 endpoints, as well as supporting a number of different file formats. Additionally, they contributed to enhancements within the Thrift interface, ensuring that certain methods were now authenticated. They were also involved in configuring features related to the codebase such as the use of code sanitization and added support for Ubuntu 20.04.
High-performance C++ library for multiphysics and multibody dynamics simulations
Role in this project:
Back-end Developer & Build Automation Engineer
Contributions:110 commits, 12 PRs, 63 pushes in 6 years 1 month
Contributions summary:Andrew primarily focused on improving the build process and fixing compilation issues. They addressed system-specific compilation problems by modifying preprocessor directives and include statements. Additionally, the user added support for CDash and auto-generated version information, demonstrating a focus on build automation and continuous integration. They also corrected code formatting, updated documentation, and fixed a memory leak.
c-plus-plussimulationroboticssimulationsmultibody
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Andrew Seidl - Principal Engineer, AI ML Infrastructure at Vultr