Computational ML Meteorologist

Computational ML Meteorologist

Join WeatherX as a Computational ML Meteorologist, diving into machine learning applications for severe weather predictions

Job Description

At WeatherX, we're not just focused on today's weather. We're laying the groundwork for the future, diving deep into the intricate interplay between machine learning, severe weather forecasting, and climatology. Join our team as a Computational Machine Learning Meteorologist and play a pivotal role in leveraging AI to decipher both current weather patterns and anticipate future climatic shifts.

Role Responsibilities

  • Develop and optimize machine learning models focused on intricate severe weather forecasting.
  • Collaborate closely with data scientists and meteorologists to design and train models that can anticipate and adapt to evolving weather patterns as influenced by larger climatic shifts.
  • Analyze and interpret data to understand the implications of global climate change on local weather patterns.
  • Provide insights on how to apply advanced statistical methods within the field of atmospheric sciences, especially emphasizing severe weather events.
  • Collaborate with the product team to ensure our tools and offerings are optimized for these future scenarios, ensuring our clients are always a step ahead.
  • Stay updated with current and evolving climatic trends and researches in both meteorology and machine learning, and strategize optimization for future climate scenarios.
  • Oversee and implement accuracy and verification processes to ensure data precision and reliability in forecasts and continuously research and implement new methodologies to improve the accuracy, efficiency, and scope of our weather models.


  • Master’s or PhD in Meteorology, Atmospheric Sciences, or related field.
  • Strong background in machine learning, with hands-on experience in popular libraries such as TensorFlow or PyTorch.
  • Proven expertise in severe weather forecasting, with a keen interest in understanding the broader implications of climate change on localized weather phenomena.
  • Ability to conceptualize and communicate the future of weather in a changing global environment.
  • Skilled at bridging the gap between traditional meteorological methods and cutting-edge technological innovations.

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