Joseph Hardin
Software Engineering Manager & Weather Forecasting Lead
California, United States
Summary
👤
Senior🎓
Top SchoolJoseph Hardin is a software engineering manager and weather forecasting lead with 14 years of experience blending digital signal processing, machine learning, and remote sensing to build production forecasting systems. Currently leading Apple’s Weather Forecasting team, he brings a rare mix of hands-on radar algorithm expertise and cloud-native engineering management honed at startups and national labs. His work spans Doppler and weather radar processing, source/channel coding, and high-dimensional data pipelines, with open-source contributions to the widely used Python ARM Radar Toolkit (pyart) improving radar data handling and reader support. At ClimateAI and PNNL he scaled ML evaluation pipelines and built Kubernetes-based platforms for cost-efficient data science workflows, cutting custom reporting times from weeks to under 24 hours. He holds a PhD in Electrical Engineering and is known for translating academic radar and signal-processing research into robust operational systems. Colleagues rely on him for mentoring teams across research, engineering, and product to deliver measurable forecasting impact.
14 years of coding experience
17 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Electrical Engineering, Doctor of Philosophy (Ph.D.) Electrical Engineering at Colorado State UniversityM.S. Electrical Engineering, M.S. Electrical Engineering at New Mexico State University
English
Github Skills (6)
py10
python10
data-visualization8
data-visualisation8
data-visualizations8
numpy8
Programming languages (8)
Github contributions (5)
ARM-DOE/pyart
Feb 2013 - Oct 2015
The Python-ARM Radar Toolkit. A data model driven interactive toolkit for working with weather radar data.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:17 commits, 6 PRs, 33 comments in 2 years 8 months
Contributions summary:Joseph primarily focused on modifying and improving the `pyart` library. Their work included correcting errors in the handling of radar data, such as non-homogeneous rays, and updating examples. The user also refactored code, corrected naming conventions, and addressed installation issues related to the RSL library, enhancing the reliability and usability of the toolkit. Furthermore, they added support for CHL reader functionality.
model-drivenpythonradar-processingradardata-driven-model
josephhardinee/pytmatrix
Sep 2015 - Nov 2015
Contributions:36 commits, 4 PRs, 35 pushes in 1 month
python-codepythoncalculationsmatrixscattering
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