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Opportunity

  • Be one of the initial hires at a remote startup, started by experienced entrepreneurs, developing a transformative approach to earth system modeling.
  • Build the world’s best weather forecast using an approach that learns directly from observational data.
  • Join a multi-disciplinary team committed to open science and sharing results with the broader weather and climate communities.

Requirements

  • MS or PhD in computer science, mathematics, machine learning, physics, atmospheric science, or equivalent industry experience.
  • Practical experience in applying experimental ideas to real-world problems.
  • Strong understanding of machine learning and statistical methods.
  • Experience with Python-based ML frameworks such as PyTorch or JAX.
  • Proficiency in running, tracking, and analyzing experiments, with the ability to instrument them with meaningful metrics and visualizations.
  • Strong troubleshooting skills to diagnose and resolve issues in machine learning workflows.
  • Ability to work independently.
  • Flexibility and adaptability to work on diverse projects and pivot when necessary.

Great to Have

  • Experience using ML architectures such as graph neural networks, transformers, or diffusion models.
  • Experience working with physical sensor data.
  • Familiarity with the basic principles of numerical weather prediction systems.

Responsibilities

  • Collaborate with the founding team to push the boundaries of observation-driven ML weather forecasting.
  • Identify and prototype promising techniques from the broader ML research community.
  • Conduct experiments, analyze results, and scale up successful approaches.
  • Develop methods for effectively handling a wide range of observational data types.
  • Work with the broader engineering team to integrate ML models into our operational weather prediction system.
  • Ensure high-quality engineering and research practices through code reviews and rigorous development standards.

Apply now