Deep Learning Meteorological Scientist

Job Description

The Weather Company is seeking a Deep Learning Meteorologist to drive innovation in weather prediction and forecasting. The successful candidate will conduct research, develop cutting-edge deep-learning methodologies, and refine models to enhance weather predictions and decision-support services. This individual will collaborate with colleagues to implement these methods in operational systems, analyze meteorological data, and stay at the forefront of AI advancements in weather forecasting.

The role involves:

• Conducting research and development of open-source deep-learning methods.
• Developing and fine-tuning deep-learning-based methods for data assimilation and forecast modeling.
• Analyzing and interpreting meteorological data from various sources.
• Validating numerical methods and comparing them against benchmarks.
• Collaborating with colleagues to implement deep-learning methods in operational systems.
• Staying updated on the latest advancements in deep-learning algorithms.
• Providing expert consultation to non-meteorologists and stakeholders.
• Representing The Weather Company and the scientific community.

Requirements include:

• A PhD in a relevant field or equivalent experience.
• 3+ years of experience in an applied meteorological or technical position.
• Experience applying deep-learning algorithms for weather-forecasting applications.
• Experience with foundation models and fine-tuning existing models.
• Deep knowledge in AI/deep learning, meteorology, programming, computing, and data science.
• Ability to work with open-source software.
• Strong collaboration skills.

The Weather Company offers:

• Flexible Time Off program
• Hybrid work model
• Variety of medical insurance options
• Benefits effective day 1 of employment
• Competitive 401K match with no vesting requirement
• National health, dental, and vision plans
• Progressive family plan benefits
• An opportunity to work for a global and industry-leading technology company
• Impactful work in a collaborative environment