Be one of the initial hires at a remote startup, started by experienced entrepreneurs, developing a transformative approach to earth system modeling.
Build the world’s best weather forecast and data analysis system using a data-driven, end-to-end learned approach.
Join a multi-disciplinary team committed to open science and sharing results with the broader weather and climate communities.
Requirements
BS, or MS in computer science, mathematics, applied statistics, machine learning, physics, meteorology, geography, or equivalent industry experience.
3+ years of industry experience developing peta-scale data infrastructure, ideally working with a multitude of geospatial data from weather/climate models, satellites, radar, and types of observation systems.
Expert proficiency in Python.
Practical experience working with diverse weather/environmental data formats, including HDF5, NetCDF, Tiff/GeoTiff, BUFR, GRIB, and various weather radar formats.
Experience and proficiency working with systems and tools designed for large-scale data processing and archival, including Parquet, Apache Beam/Google Cloud Dataflow, BigQuery, or equivalent systems and tools on AWS or Azure.
Experience designing, rapidly prototyping, and evaluating complex data processing systems
Proficiency in communicating system designs to and with input from technical stakeholders including scientists and engineers.
Ability to work independently.
Flexibility and adaptability to work on diverse projects and pivot when necessary.
Great to Have
Knowledge about weather and climate observation systems and data, especially from satellite platforms.
Familiarity with NOAA/NASA/ESA/JAXA satellite data and other datasets commonly leveraged for numerical weather prediction and data assimilation applications.
Familiarity developing in Fortran, C++.
Familiarity with common open-source tools developed in the world of weather/climate for interacting with legacy data, including eccodes package from ECMWF and the various NCEPLIBS-* from NOAA.
Experience collaborating or working with stakeholders from diverse communities, including academic researchers and civil servants working at NOAA or similar agencies.
Hands-on experience designing and building applications on Google Cloud Platform leveraging managed services/products.
Expertise in designing data systems which feed into large-scale AI/ML model training and inference.
Responsibilities
Collaborate with the founding team to advance the state of the art in weather forecasting using a data-driven, end-to-end learned approach.
Design and implement peta-scale data processing systems for building AI/ML-ready datasets core to the company’s scientific research and product portfolio.
Work closely with the research team to design and generate datasets for AI/ML modeling.
Help develop and implement standards and frameworks for creating AI/ML-ready weather/climate observational datasets, and use these to publish datasets developed as part of the company’s scientific research agenda.
Establish best practices and workflows for data engineering across the company’s development portfolio.
Promote engineering best practices by conducting code reviews and ensuring high-quality code.