Johan Jino
System Software Engineer at Imperial College London
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolJohan Jino is a system software engineer at NVIDIA with four years of experience focused on system performance, computer architecture and compiler-driven optimizations. Trained at Imperial College London (MEng), he blends research-minded hardware–software co-design with hands-on work on GPUs and FPGAs, having progressed from internships at Qualcomm and NVIDIA to a full-time role. He contributed to the cross-framework ML library ivy, improving statistical primitives and backend compatibility across TensorFlow, PyTorch and JAX, showing an eye for portability and testing. As an undergraduate teaching assistant, he also mentors peers and translates low-level concepts into practical learning, revealing a knack for clear technical communication.
4 years of coding experience
1 year of employment as a software developer
Master of Engineering - MEng Computer/Electronic and Information Engineering, Master of Engineering - MEng Computer/Electronic and Information Engineering at Imperial College LondonAll India Senior School Certificate Examination Science Stream, All India Senior School Certificate Examination Science Stream at GEMS Education
English, French, Hindi, Malayalam
Github Skills (15)
statistics10
machine-learning10
python10
stat10
statistic10
converter10
transpiler9
numpy9
jax9
tensorflow9
deeplearning-ai9
deep-learning9
transcode9
pytorch9
testing8
Programming languages (6)
Github contributions (5)
ivy-llc/ivy
Jun 2022 - Oct 2022
Convert Machine Learning Code Between Frameworks
Role in this project:
ML Engineer
ML EngineerContributions:7 reviews, 27 commits, 44 PRs in 3 months
Contributions summary:Johan primarily contributed to the development and maintenance of the `ivy` library, a tool for converting machine learning code between frameworks. Their work focused on implementing and testing statistical functions (min, max, mean, var, std, prod, sum) across different backends (TensorFlow, PyTorch, Jax) which suggests a focus on ensuring cross-framework compatibility. They also worked on test improvements, and added frontend functionalities like Maximum, Minimum, Floor, and Sinh operations.
pythontensorflowframework-learningtemplatedata-science
johanjino/johanjino.github.io
Sep 2022 - Aug 2024
Contributions:25 pushes, 1 branch in 1 year 11 months
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