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.

Please note that this position is a hybrid role, and the team collaborates in person twice weekly at our Golden, Colorado office.

• 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.

This position requires access to technology that is controlled under U.S. export control laws and regulations. Accordingly, this position is restricted to U.S. citizens, permanent residents and protected individuals unless and until any required licenses are obtained.

Tomorrow.io is proud to be an Equal Employment Opportunity and Affiliated 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.

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…