Machine Learning Scientist

The R&D Team  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 to help improve Tomorrow.io's weather forecast performance to deliver more accurate weather insights to our customers. In this role, you will apply atmospheric science knowledge and modern machine learning techniques to develop, evaluate, and operationalize forecast improvements across Tomorrow.io's weather products. You will work collaboratively from proof-of-concept through deployment, focusing on measurable gains in forecast skill and reliability in an operational environment.

• Conduct innovative research at the intersection of weather prediction and machine learning, including approaches that leverage observations from Tomorrow.io’s satellite constellation.
• Develop, verify, and document forecast improvements that provide measurable value to customers.
• Partner with engineering and product teams to transition research advances into scalable, operational systems.
• Communicate results through internal reviews, customer discussions, and, where appropriate, conferences or publications.
• Contribute broadly to improving Tomorrow.io’s forecast skill and overall product performance.

• Graduate degree in atmospheric science, meteorology, computer science, or a related field.
• 2+ years of professional experience applying deep learning to weather prediction or related geoscience problems.
• Strong machine learning engineering fundamentals, including model training, validation, evaluation, and documentation.
• Experience working in cloud-based computing environments.
• Experience handling large meteorological datasets and common data formats at scale.
• Experience with modern deep learning frameworks (e.g., PyTorch or Tensor Flow).
• Strong written and verbal communication skills.
• Ability to manage multiple projects and balance competing priorities.

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.

Selected by TIME Magazine as one of the Top 100 Most Influential Companies in the World, Tomorrow.io is the world’s leading Resilience Platform. Combining next-generation space technology, advanced generative AI, and proprietary weather modeling, Tomorrow.io delivers unmatched forecasting and decision-making capabilities. Trusted by six of the top ten Fortune 500 companies, Tomorrow.io empowers organizations to proactively manage weather-related risks, opportunities, and enhance operational efficiency.

From cutting-edge weather intelligence to real-time early warning systems, Tomorrow.io enables predictive, impact-based action for a safer, more resilient future. Learn more .

Our ethos guides us in everything we do - The people of Tomorrow are here to make an impact, they show true grit, and always put people first.

We work in an "one office" environment. We believe that magic happens when people work together. Together also includes Zoom meetings, flexible hours and unlimited vacation days. Your success is achieved by your impact and deliveries and not by the hours you put in. We believe in transparency and directness, putting work before ego and empathy. We grow fast and move faster but we always see people first.

Each person has their own career growth path for we believe that the only way for the company to grow is if you grow.