Jon Bosque is Head of Machine Learning with eight years of experience building production ML systems for industrial optimization and automation. He moved from modeling option markets and algorithmic trading in his undergrad to spiking neural networks and control-aware ML in his master's, blending reinforcement learning, control theory and practical engineering. At Optimitive he rose from R&D ML engineer to lead, shipping tools that help engineers optimize industrial processes and contributing to open-source ecosystems—including lint improvements to the widely used rust-clippy project. Based in Greater Bilbao, he combines hands-on coding (Rust backend contributions) with domain expertise in mechatronics, robotics and automated trading, and keeps exploring the intersection of ML and control to make systems both intelligent and reliable.
8 years of coding experience
5 years of employment as a software developer
Master's Degree on Industrial Engineering Mechatronics Robotics and Automation Engineering, Master's Degree on Industrial Engineering Mechatronics Robotics and Automation Engineering at Universidad del País Vasco/Euskal Herriko Unibertsitatea
A bunch of lints to catch common mistakes and improve your Rust code. Book: https://doc.rust-lang.org/clippy/
Role in this project:
Backend Developer
Contributions:26 reviews, 3 PRs, 51 comments in 2 months
Contributions summary:Jon primarily focused on improving the `clippy_lints` codebase by adding new lints and refining existing ones. They implemented a new lint related to unnecessary use of `map`/`map_err` on Option or Result constructors. Additionally, they fixed an issue in the `enum_variants` lint and introduced a new lint for struct field names. Their contributions involved modifying existing lint logic and adding tests to ensure the correct behavior of the lints.
Contributions:22 commits, 14 pushes, 1 branch in 7 months
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Jon Bosque - Head Of Machine Learning at OPTIMITIVE Group