Machine Learning Researcher

Summary

Identify and prioritize high-value ML problems across research and operations, build working prototypes, and deliver operational models that improve atmospheric-state estimation, forecasting of supercooled liquid water, retrievals, and intervention analysis. Combine multimodal data (radar, satellite, UAS, in-situ, NWP) to create datasets, baselines, uncertainty-aware evaluations, and productionizable prototypes while collaborating closely with meteorologists, engineers, and operators. Rapidly move from experiments to usable models, characterizing calibration, failure modes, and operational value to inform repeated field campaigns and interventions.