We are seeking a
Machine Learning Scientist with experience in AI weather prediction to help advance Tomorrow.io's next-generation forecasting capabilities. In this role, you will combine atmospheric science expertise with state-of-the-art machine learning methods to improve forecast skill, including developing new ways to leverage observations from Tomorrow.io's microwave sounder constellation. You will work collaboratively from proof-of-concept through deployment, with a focus on translating research advances into operational, customer-impacting products.
What you'll do:- Conduct research and development at the intersection of machine learning and weather prediction.
- Develop, train, evaluate, and improve AI-based weather prediction models, with a focus on measurable improvements in forecast skill and customer value.
- Develop approaches to maximize the value of observations from Tomorrow.io's satellite constellation for weather prediction.
- Explore machine learning approaches for incorporating observations into forecast systems, including ML-based data assimilation and related methods.
- Work with large atmospheric and geophysical datasets and build reproducible, maintainable ML workflows.
- Collaborate with scientists and engineers to transition successful research from proof-of-concept into scalable, operational systems.
- Communicate results clearly through internal reviews, technical discussions, and, where appropriate, conferences and peer-reviewed publications.
What you bring:- Graduate degree in atmospheric science, meteorology, computer science, or a related quantitative field.
- 2+ years of experience developing machine learning approaches for weather prediction or closely related geoscience problems. Relevant PhD research developing ML models may count toward this experience.
- Hands-on experience training, evaluating, and working with deep learning models for atmospheric science.
- Strong understanding of ML development best practices specific to atmospheric science, including experimental design, model evaluation, testing, documentation, and code review.
- Strong written and verbal communication skills and the ability to explain complex technical results to both technical and non-technical audiences. Demonstrated ability to collaborate across disciplines and deliver high-quality work.
- Experience conducting independent research, demonstrated through publications, research leadership, open-source contributions, or other technical work.
Nice to have:- Knowledge of or experience with data assimilation, including traditional and/or machine-learning-based approaches, is a strong plus.
- Knowledge of satellite remote sensing and experience working with satellite observations.
- Experience developing production-quality scientific or machine learning software.
- Familiarity with modern architectures used in weather and geoscience ML, including graph neural networks and transformers.
- AI-first mentality towards research and development (e.g., using AI-assisted development tools)
The anticipated salary range for this role is $145k-$160k subject to local market and candidates skills and experience. Comprehensive health benefits, unlimited paid time off and other benefits included. Relocation assistance may be offered/available for certain roles.
