Michael Aquilina is a software engineer with 13 years of experience building high-performance, cloud-native systems and machine learning infrastructure across startups and security-focused companies. With a First Class master's in Machine Learning, Data Mining and High Performance Computing from the University of Bristol, he bridges rigorous academic training and hands-on production work, particularly in AI/ML, security data, and HPC parallelisation (OpenMP, MPI, OpenCL). He has held senior and staff engineering roles at Snyk and Lyst and now works on AI-focused products, contributing to both product engineering and ML model deployment on AWS/Linux. An active open-source contributor, Michael has improved core Python tooling and test suites for projects like pytest and dateutil, and wrote a practical ZSH plugin to streamline developer workflows. Comfortable across Python, C and C#, he pairs strong mathematical foundations with a knack for automating and hardening UNIX-like environments. Outside work he blends interests in astronomy and bioinformatics, often publishing personal projects and tooling on GitHub.
13 years of coding experience
14 years of employment as a software developer
Bachelor's Degree Computer Science and Artificial Intelligence, Bachelor's Degree Computer Science and Artificial Intelligence at University of Malta
www.coursera.com
Master's Degree Machine Learning Data Mining and High Performance Computing, Master's Degree Machine Learning Data Mining and High Performance Computing at University of Bristol
📎 ZSH plugin that reminds you to use existing aliases for commands you just typed
Role in this project:
Back-end Developer
Contributions:13 reviews, 277 commits, 135 PRs in 5 years 8 months
Contributions summary:Michael primarily contributed to the development and refinement of a ZSH plugin. Their work included implementing the core functionality of the plugin, specifically the alias checking feature and adding new modes. Further, the user added functionalities such as global and git alias support, alongside enhancing the plugin with hardcore mode features. Moreover, the user's contributions also include refactoring and cleaning up the codebase and optimizing for edge cases, such as making messages use `printf`.
The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
Role in this project:
QA Engineer / Test Automation Engineer
Contributions:6 PRs, 22 comments in 7 months
Contributions summary:Michael primarily contributed to improving the test suite for the `pytest` framework. Their commits focused on adding, updating, and expanding tests related to skipping tests with `@pytest.mark.skip`, including handling different skip conditions and reasons. They added tests for class-level skipping and ensured the correct behavior of skipping with various configurations. Their work improved test coverage and addressed edge cases related to test skipping functionality.
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Michael Aquilina - Software Engineer at Geordie AI