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Opportunity

  • 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 using an approach that learns directly from observational data.
  • 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 data ingestion and processing infrastructure, ideally working with a multitude of geospatial data from weather/climate models, satellites, radar, and types of observation systems.
  • Expert proficiency in Python.
  • Hands-on experience designing and building applications on Google Cloud Platform leveraging managed services/products.
  • 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, Zarr, Apache Beam/Google Cloud Dataflow, BigQuery, etc.
  • 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

  • Experience leveraging workflow orchestration tools to automate data processing pipelines, such as Dagster, Airflow, or Prefect.
  • 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 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.

Responsibilities

  • Collaborate with the founding team to push the boundaries of observation-driven ML weather forecasting.
  • Design, implement, and operationalize terascale weather data ingestion and processing systems, optimizing for low latency and frictionless integration into ML workflows.
  • Work closely with core research and engineering staff to coordinate and prioritize dataset acquisition and preparation.
  • 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.

Apply now