Juan Martinez
Software Engineer at Momentus
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJuan Martinez is a software engineer with nine years of experience building simulation, ML productivity tools, and operational software for space and enterprise systems. Based in Palo Alto, he currently accelerates machine learning development at Google while also designing flight modeling and simulation stacks for satellite operations at Momentus. His background blends physics and CS (BS) with an MS in Aerospace from Stanford, enabling him to move fluidly between low-level performance work and high-level system modeling. He has contributed to TensorFlow internals—refactoring for constexpr, removing lazy loads, and resolving circular dependencies—highlighting a focus on build performance and maintainability in large open-source projects. Earlier roles range from production automation with computer vision to security API integration and research on nanoscale devices, showing curiosity across hardware, software, and operations. He is motivated by Guidance, Navigation, and Control challenges in the space industry and brings both operational experience and tooling expertise to that pursuit.
9 years of coding experience
1 year of employment as a software developer
Bachelor's degree, Physics and Computer Science, Bachelor's degree, Physics and Computer Science at Florida State UniversityMaster of Science - MS, Aerospace, Aeronautical and Astronautical Engineering, Master of Science - MS, Aerospace, Aeronautical and Astronautical Engineering at Stanford University School of Engineering
Github Skills (11)
c-language10
cprogramming-language10
tensorflow10
optimization9
optmization9
performance-optimization9
optimisation9
machine-learning9
deep-learning9
compiler-development8
python8
Programming languages (4)
Github contributions (5)
tensorflow/tensorflow
Aug 2022 - Jan 2023
An Open Source Machine Learning Framework for Everyone
Role in this project:
Back-end Developer
Back-end DeveloperContributions:55 commits, 2 PRs, 36 pushes in 4 months
Contributions summary:Juan primarily focused on internal code changes and refactoring within the TensorFlow codebase. Their work involved modifying code to use `constexpr` instead of `const` in the compiler, likely for performance improvements. Additionally, they removed unused lazy loads, updated Clang toolchain configurations, and refactored code to address circular dependencies. This indicates a focus on code quality, maintainability, and build/performance optimizations within the project.
pythondata-sciencedeep-learningmlmachine-learning
jam14j/BookScorePredictor
Apr 2020 - May 2020
Contributions:9 pushes, 1 branch in 24 days
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