Machine Learning Researcher

About Rainmaker Rainmaker is pioneering a modern cloud-seeding system to increase precipitation, improve water availability, and address severe-weather challenges. We combine atmospheric science, weather-resistant UAS, radar and satellite observations, numerical weather prediction, novel sensing systems, and sustainable seeding technologies to design, operate, and evaluate precipitation-enhancement programs. Research at Rainmaker is attached directly to operations. Our scientists and engineers collect proprietary observations, deliberately intervene in atmospheric systems, evaluate the results, and use what they learn to improve the next operation. About the Role Rainmaker is hiring its first dedicated Machine Learning Researcher. You will establish how Rainmaker uses machine learning across the company: identifying the most valuable problems, determining which are ready for ML, building working models, and partnering with engineers and domain experts to turn successful research into operational systems. You will not inherit a single predetermined model roadmap. The opportunity set includes forecasting supercooled liquid water and cloud-seeding opportunities, assimilating multimodal observations into estimates of atmospheric state, improving microwave-sounder retrievals, predicting hail, learning from intervention outcomes, and finding other high-leverage applications across research and operations. Rainmaker's long-term advantage is not a generic weather model. It is the combination of proprietary in-cloud observations, radar and satellite data, UAS measurements, field campaigns, and repeated atmospheric interventions. You will build the learning systems that turn those data into better estimates, predictions, and decisions. This is initially a hands-on individual-contributor role. You may eventually help recruit or technically lead an ML team if that fits your strengths and Rainmaker's needs, but management is not an initial expectation.