Machine Learning Scientist

About this role

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 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)

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.

Tomorrow.io is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Tomorrow.io participates in the E-Verify program in all US states, as required by law.

At tomorrow.io we have established a workplace culture that values fairness and equal opportunities and we believe it is crucial for fostering a positive and productive environment. Regularly reviewing and adjusting pay practices to align with legitimate drivers of pay, such as job level, geographic location, and performance, demonstrates a commitment to maintaining equity within the organization.This commitment to ongoing assessment and improvement is key to creating a workplace that is not only diverse and inclusive but also fair and just. 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.

Tomorrow.io is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at jobs@tomorrow.io

About Tomorrow.io:

Tomorrow.io is helping Countries, Businesses and Individuals better manage their Climate Security Challenges. Fully customizable to any industry impacted by the weather, customers around the world including Uber, Delta, Ford, National Grid and more use Tomorrow.io t

Similar jobs

• Machine Learning Scientist — Cartesiansystems · Cambridge, MA
• Machine Learning Scientist — Suno · Boston
• Machine Learning Scientist III — Expedia · Washington - Seattle Campus
• Senior Machine Learning Scientist — Axon · Boston, Massachusetts, United States
• Senior Machine Learning Scientist — Axon · Seattle, Washington, United States
• Senior Machine Learning Scientist — Axon · Scottsdale, Arizona, United States
• Senior Machine Learning Scientist — Teladoc · Remote
• Senior Machine Learning Scientist — Expedia · Washington - Seattle Campus | San Jose, California, United States