Jonathan Reich
Agentic AI Engineer at Acenda
Melbourne, Victoria, Australia
Summary
👤
Senior🎓
Top SchoolJonathan Reich is an Agentic AI Engineer and Data Scientist based in Melbourne with nine years of experience building end-to-end ML systems across NLP, predictive modeling and computer vision. He has delivered production solutions in regulated domains—government online dispute resolution and private healthcare—using bespoke neural networks, open-source LLM workflows (RAG, QLoRA/LoRA) and distributed training/inference with DeepSpeed and accelerate. Comfortable across Python, Java, R, SQL, C/C++ and Scala, he integrates models into AWS and Azure pipelines and brings hands-on expertise with PyTorch and TensorFlow. An iAward winner and CRN Impact Award nominee, he also contributes to prominent open-source tooling—such as a maintenance and API-improving patch to scikit-image’s hessian_matrix—demonstrating attention to long-term code quality. His background in bioinformatics, classics and languages gives him an uncommon blend of technical rigor and cross-disciplinary perspective useful for novel ML applications.
9 years of coding experience
5 years of employment as a software developer
The University of MelbourneBachelor of Science, Major in Biochemistry, Minors in Computer Science and Statistics, Bachelor of Science, Major in Biochemistry, Minors in Computer Science and Statistics at Monash University
Spanish, Hebrew, Latin, Greek
Github Skills (7)
computer-vision10
scikit-image10
python10
image-processing10
numpy10
testing9
documentation8
Programming languages (3)
Github contributions (5)
scikit-image/scikit-image
Oct 2016 - Apr 2017
Image processing in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:32 commits, 6 PRs, 17 comments in 6 months
Contributions summary:Jonathan primarily contributed to the `scikit-image` project by modifying the `hessian_matrix` function. Their work involved adding and adjusting the `order` parameter, which impacts the ordering of Hessian matrix values. They also addressed deprecation warnings related to the `order` parameter, updated the documentation, and refactored existing code to improve maintainability and ensure future compatibility. Their changes directly influenced the image processing capabilities.
image-processingpythoncomputer-visionimage
JohnnyTeutonic/view_all
Jul 2017 - Dec 2024
Contributions:6 PRs, 74 pushes, 4 branches in 7 years 6 months
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