Provides full-stack software support across a range of data infrastructure projects. Ensures the code behind the multi-scale climate modeling project is reproducible, performant, and delightful for outside contributors. Responsible for prototyping surrogate models and machine‑learned emulators trained on targeted high‑resolution simulations, designed to increase the accuracy and speed of modeling SAI deployment scenarios.
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USD/year
USD/year
This position plays a critical role in the research-to-operations (R2O) process by enabling the integration of new models, data sources, and processing workflows into operational test environments. The role requires strong programming and analytical skills, a solid understanding of geophysical or atmospheric data, and the ability to work collaboratively with scientists, developers, and operational forecasters.