Kyle Reeve
Principal Embedded Software Engineer at 10Beauty
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolKyle Reeve is a Principal Embedded Software Engineer with 11 years of experience building robotics, perception, and ML-driven systems, currently based in Boston. He progressed through multiple senior engineering roles at Amazon — including Prime Air and Amazon Robotics — where he delivered production-grade embedded and autonomous software. His background bridges mechanical engineering (B.S., Northeastern) and advanced CS (M.S. candidate, Georgia Tech), enabling pragmatic design of hardware-near algorithms and control systems. An active open-source contributor, he improved shrinking algorithms and test automation in the widely used Hypothesis property-testing library, helping reduce non-minimal failing examples. Kyle combines rigorous testing and automation practices with machine-learning insights to make complex robotic systems more reliable in the field. Colleagues describe him as a hands-on engineer who moves fluid research into robust production deployments.
11 years of coding experience
11 years of employment as a software developer
Driscoll/BHSMaster of Science (M.S.) Computer Science, Master of Science (M.S.) Computer Science at Georgia Institute of TechnologyBachelor of Science (B.S.) Mechanical Engineering, Bachelor of Science (B.S.) Mechanical Engineering at Northeastern UniversityBHS
Github Skills (8)
algorithm10
property-based-testing10
data-structures10
algorithms10
python10
data-structure10
testing10
fuzzing9
Programming languages (3)
Github contributions (5)
HypothesisWorks/hypothesis
Feb 2018 - Mar 2018
The property-based testing library for Python
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:22 commits, 1 PR, 8 comments in 5 days
Contributions summary:Kyle primarily contributed to the testing and shrinking logic of the hypothesis testing library. They focused on implementing and refining shrinking algorithms, specifically those related to offset pairs and block manipulations within the conjecture engine. The user also added tests to cover the new shrinking features, improving the library's ability to minimize failing test cases and reducing non-minimal examples. Furthermore, the user made improvements to the library documentation and overall codebase.
property-based-testingpythontestingfuzzing
kreeve/hypothesis-python
Feb 2018 - Mar 2018
Contributions:21 pushes, 1 branch in 4 days
property-based-testingtestingflexible
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