Jonathan Malmaud
Senior Research Engineer at Google DeepMind
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJonathan Malmaud is a Senior Research Engineer with 14 years of experience building ML systems and developer tooling at Google and Google DeepMind, focused recently on LLMs for software engineering tasks. He blends deep research training (PhD-level machine learning from MIT) with hands-on engineering across front-end and back-end stacks, demonstrated by significant open-source contributions to Julia, Jupyter tooling (IJulia), CodeMirror, and Visdom. His work spans low-level language/runtime improvements in the Julia core, interoperable bindings (PyCall, TensorFlow.jl), and developer-facing features like syntax highlighting and Plotly support—showing fluency across languages and layers. At Google he has shipped research and engineering on neural network quantization, fine-tuning, prompt engineering, data curation, and evaluation for practical SE applications. He also has a track record of applied research internships (Vision, multimodal alignment, and probabilistic extraction) and publications, indicating the ability to move ideas from papers to production. Based in Mountain View, he combines research rigor with production-grade software craftsmanship, often improving developer experiences in non-obvious corners like editor modes and language kernels.
14 years of coding experience
5 years of employment as a software developer
PhD Machine learning, PhD Machine learning at Massachusetts Institute of TechnologyCalifornia Institute of Technology
Github Skills (37)
javascript10
visualization10
interoperability10
back-end-development10
python10
jupyter10
operation10
tensorrt10
numpy10
regular-expression10
tensorflow10
tensor10
visualizations10
codemirror10
syntax-highlighting10
Programming languages (16)
Github contributions (5)
malmaud/TensorFlow.jl
Jun 2016 - Aug 2021
A Julia wrapper for TensorFlow
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:33 releases, 1 review, 831 commits in 5 years 2 months
Contributions summary:Jonathan made improvements and added functions to the `tensorflow.jl` repository, a Julia wrapper for TensorFlow. Their contributions primarily involved implementing several operations and functions for working with tensors, including methods for handling various mathematical operations and reductions. Furthermore, they added support for variable creation, management, and saving/restoring functionality within the TensorFlow framework.
julia-wrappermlmachine-learningtensorflowjulia
JuliaLang/IJulia.jl
Oct 2013 - Jan 2017
Julia kernel for Jupyter
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:19 commits, 2 PRs, 3 pushes in 3 years 3 months
Contributions summary:Jonathan primarily contributed to the development of syntax highlighting for the Julia language within the Jupyter environment, as evidenced by the numerous changes to the `julia.js` file. Their work involved adding support for various Julia syntax elements, including symbols, backticks, and fixing parsing errors. Furthermore, they made improvements to the build process, including enabling syntax highlighting in the QT Console and adding pre-execute hooks, and refining the code.
kernelapljupyter-notebooknotebookjupyter
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