Juan Borrego
Machine Learning Engineer at AiFi Inc.
Cerdanyola del Vallès, Catalonia, Spain
Summary
👤
Senior🎓
Top SchoolJuan Borrego is a Machine Learning Engineer with eight years of experience building and deploying efficient deep learning systems across cloud and edge environments. He blends research-grade expertise in computer vision and time-series with production skills in Kubernetes, Databricks/MLflow, TensorRT/OpenVINO and model optimization (quantization, pruning, NAS) for resource-constrained targets. His background spans academia and industry—from bronchoscopy navigation research and Samsung mobile CV work to leading embedded ML efforts at KOSTAL and production GPU orchestration at AiFi. An active open-source contributor, he has contributed kernel-level work to the gpytorch project, reflecting a comfort with core ML tooling and Gaussian process implementations. Based in Cerdanyola del Vallès, he pairs a physics and data-science education with PhD-level AI research, making him adept at translating advanced models into robust, deployable systems.
8 years of coding experience
4 years of employment as a software developer
Degree, Physics, Degree, Physics at Universitat Autònoma de BarcelonaResearch Stage, Research Stage at Mälardalens högskolaM.Sc. Foundations of Data Science, Data Science, M.Sc. Foundations of Data Science, Data Science at Universitat de Barcelona
Stackoverflow
805reputation
94kreached
47answers
2questions
Github Skills (9)
pytorch10
python10
keras6
machine-learning6
anaconda6
linux6
tensorflow6
scikit-learn6
ubuntu6
Programming languages (4)
Github contributions (5)
cornellius-gp/gpytorch
Jan 2020 - May 2020
A highly efficient implementation of Gaussian Processes in PyTorch
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits, 1 PR, 15 comments in 3 months
Contributions summary:Juan primarily contributed to the `arc_kernel.py` file, which implements the Arc Kernel. Their commits involved merging branches, indicating active development and integration efforts. The user appears to be modifying the core kernel functionality and integrating it with existing code, as seen in the edits to test files and other files.
pytorchgpu-accelerationgaussianstochastic-processesmodular
BCJuan/SpArSeMod
Apr 2020 - Nov 2020
SpArSeMod: automatic CNN and RNN architectures for microcontrollers
Contributions:10 commits, 45 pushes, 2 branches in 7 months
architecturesrnndeep-learningtensorflowmicrocontrollers
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