The R&D Team at Tomorrow.io is a dynamic mix of scientists and engineers. Our mission is to generate the best and most novel data and models across all times: historical, real-time, and forecast. The story just begins when the data hits our ingest and post-processing services. Every product that the user sees is the result of a pipeline of algorithms that needs to be run quickly and continuously, in an operational environment. We are the team that builds the architecture behind the data and the models, preparing the weather analyses for the Product and Engineering team to serve the masses.

We are seeking an Atmospheric Data Scientist with experience in machine learning and atmospheric or related sciences. As an Atmospheric Data Scientist, you will blend your subject matter expertise and state-of-the-science machine learning algorithms to advance weather prediction capabilities. You will be part of a team of dedicated scientists and engineers that are seeking innovative ways to improve the state of weather forecasting and satellite product development using Machine Learning toolkits. Work will involve developing on our existing operational product pipelines and bringing new projects from the POC phase to completion and deployment.

Please note that this is a hybrid position, and will include days to work from home, as well as days to collaborate with teammates in-office.

What you'll do: - Conduct innovative research to leverage Tomorrow.io's satellites in weather forecasting - Collaborate across the team to develop, execute and document research at the intersection of satellite meteorology and deep learning - Partner with internal teams to transition research breakthroughs into scalable, operational products - Share project outcomes through professional conferences, publications, and client presentations - Contribute to broad objectives to improve Tomorrow.io's weather products and support the end-to-end delivery of skillful forecasts to our customers

What you bring: - Graduate degree in atmospheric science, meteorology or related field - At least 3 years of professional (post-graduate) experience working with modern (deep) machine learning applications in the geosciences - Demonstrated experience with the best practices in ML model development, testing, reviewing, documenting - Experience working with cloud-based environments and services (e.g., GCP, AWS, Azure) - Demonstrated experience working with meteorological data formats (e.g., GRIB, NetCDF, etc) and large amounts of data - Demonstrated experience with any deep learning modeling framework (e.g. Pytorch, TensorFlow) - Strong communication skills: Including presenting and distilling complex topics and findings to stakeholders of diverse backgrounds - Demonstrated ability to manage multiple projects, prioritize competing efforts, and deliver on schedule and budget

So, if you're looking to join a team that is not only at the forefront of innovation but also working towards building the biggest weather platform in the world, this is the place for you! If your experience is close but only fulfills some requirements, please apply. Tomorrow.io is on a mission to build a special company. We are focused on hiring people with different backgrounds, perspectives, and experiences to achieve our goal.

If your experience is close but doesn't fulfill all requirements, please apply. Tomorrow.io is on a mission to build a special company. To achieve our goal, we are focused on hiring people with different backgrounds, perspectives, and experiences.