Collaborate with colleagues and the Unidata community to reduce the ‘time to machine learning’, through the development of conventions and best practices, as well as identifying improvements to existing Unidata software. By actively working with our community to determine how they are harnessing Artificial Intelligence/Machine Learning (AI/ML) approaches to data analysis, a convention for storing data/metadata in an AI/ML ready/friendly way can be developed. In addition with this effort, existing tools such as the MetPy and Siphon python libraries and the netCDF libraries will be evaluated for fitness, in the context of AI/ML applications. Work will be done to identify and implement improvements, to allow for smoother integration into a modern AI/ML pipeline.
Unidata supports the earth science research and education community with data and software tools. Unidata software products are used widely in the climate and other earth sciences. Unidata’s small team environment affords opportunities to work with high levels of autonomy, excel individually, and contribute to the team’s success.
View the job posting/application for further details of responsibilities and requirements.