ML Scientist for Weather & Climate Systems

ECMWF; Reading; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Hybrid working model

Salary scales & allowances

Job summary

ECMWF, based in Reading, UK, seeks a Machine Learning Scientist to develop world-leading ML models for weather and climate and to build scalable, sustainable software infrastructure. The role requires collaboration across interdisciplinary teams and with ECMWF’s national and international partners.

You will work on Anemoi, WeatherGenerator, and related Horizon Europe projects, supporting operational weather prediction and digital twin initiatives within the Earth system modelling program.

Qualifications

• Advanced degree in a physical, mathematical, data/machine learning or environmental science field.
• Experience in machine learning and software development best practices.
• Experience in Earth system modelling is desirable.
• Experience in HPC or large data science projects is desirable.

Responsibilities

• Contribute to an efficient and sustainable software infrastructure for world‑leading ML models.
• Support evolution of Anemoi and ensure code quality and longevity.
• Maintain and improve the WeatherGenerator code base.
• Explore new ML architectures for Earth system modelling.
• Implement and evaluate models and training protocols for weather forecasting.

Skills

ML model development

Testing & code review

HPC experience

English communication

Team collaboration

Software development

Education

Advanced degree in a relevant field

Tools

Anemoi library

WeatherGenerator

Job description

ECMWF, based in Reading, UK, seeks a Machine Learning Scientist to develop world-leading ML models for weather and climate and to build scalable, sustainable software infrastructure. The role requires collaboration across interdisciplinary teams and with ECMWF’s national and international partners.

You will work on Anemoi, WeatherGenerator, and related Horizon Europe projects, supporting operational weather prediction and digital twin initiatives within the Earth system modelling program.