Research Engineer, Climate Modeling
About this role
Adapting the training pipeline and data needs of NeuralGCM to run efficiently on Google Cloud resources and on NVIDIA GPUs constitutes the core daily focus of the Research Engineer. Working within the Climate Modeling team at The Allen Institute for Artificial Intelligence, this individual helps build an open-source, AI-first climate model capable of multidecadal forecasts that improve upon current physics-based climate models. The role exists to support a three-year grant project funded by google.org aimed at developing the NeuralGCM+ model, incorporating physical principles to ensure the system generalizes accurately to unseen future climates. Ideal candidates possess a background in computational science or related fields, bringing practical experience with machine learning training codes and cloud environments to a collaborative team of scientists and engineers.
What you will do
- Adapt the training pipeline and data requirements of NeuralGCM to operate efficiently on NVIDIA GPUs and Google Cloud resources.
- Document the training pipeline thoroughly and distribute code through a public GitHub repository.
- Implement and test strategies for coupling NeuralGCM with a selected machine learning ocean model.
- Engage in open-source code development alongside a tightly connected team through daily meetings, code reviews, and design documents.
- Develop and present tutorials regarding NeuralGCM+ for interested user groups and external collaborators.
What you need
- Possess two to four years of experience building and deploying a relevant machine learning application in a practical or academic research setting.
- Demonstrate fluency in Python along with collaborative coding practices.
- Hold a Bachelor of Science degree in computer or computational science, atmospheric science, a related geophysical science, or applied mathematics and statistics.
- Demonstrate experience in developing machine learning training code for deployment within a cloud computing environment.
- Exhibit excellent communication skills.
Nice to have
- Ph.D. in computer or computational science, atmospheric science, a related geophysical science, or applied mathematics/statistics, with at least one peer-reviewed first-authored publication or accepted conference paper utilizing machine learning in a physical science setting.
- Formal training or practical experience involving physically-based atmospheric, oceanic, or related model development.
- Experience writing machine learning code in JAX.
Benefits
- Generous bonus plans for a competitive compensation package
- Generous paid vacation and sick leave
- Family leave
Skills and tech stack
Questions candidates ask
What is the remote work policy for this position?
Persons in these roles are expected to work from the offices in Seattle. On-site requirements vary based on position and team.
What is the salary range for this role?
The base salary range is $146,880 to $220,320, supplemented by generous bonus plans to provide a competitive compensation package.
What is the expected duration of this role?
This position has a three-year term supported by a grant with a current period of performance ending September 22, 2029. Continuation beyond that date depends on renewal, extension, or identification of additional funding.
The application is on the official The Allen Institute for Artificial Intelligence careers page.
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