Data Science Scientific Software Engineer –Data-Driven Climate Models

Met Office; Exeter; Híbrido; GBP 35.000 - 51.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Civil Service pension with employer 28

RRA market supplement £2,000 per annum

Annual leave 27.5–32.5 days

Descripción de la vacante

The Met Office is seeking an exceptional Scientific Software Engineer to advance AI4Climate initiatives by combining machine learning with climate science, developing scalable models and explainable approaches.

You will join a multidisciplinary team of climate scientists, data scientists and software engineers, contributing to research, collaboration with partners, and publication of high-impact results that improve weather prediction and climate understanding.

Formación

• PhD or equivalent in applying ML/AI to scientific/environmental datasets.
• Strong Python and ML libraries experience and QA processes.
• Experience developing robust, maintainable, reproducible code in a scientific context.
• Ability to design experiments and evaluate methods to answer scientific questions.
• Understanding of statistical modelling, ML evaluation or uncertainty assessment.
• Experience working collaboratively in interdisciplinary teams.
• Ability to communicate complex ideas clearly to technical and non-technical audiences.

Responsabilidades

• Develop and apply machine learning and deep learning methods for climate-focused tasks.
• Design, train and evaluate data-driven climate models.
• Investigate robustness, uncertainty and physical realism of models.
• Develop approaches integrating physical understanding with ML methods.
• Design evaluation frameworks for model skill and credibility.
• Contribute to Earth system data science research.
• Collaborate with climate scientists and software engineers.
• Contribute to AI4Climate programme and Met Office strategy.
• Publish high-impact research and collaborate internationally.

Conocimientos

PhD in ML/AI

Python programming

Experimental design

Communication skills

Educación

PhD in ML/AI or related field

Herramientas

Python ML libraries

Descripción del empleo

We’re looking for an exceptional Scientific Software Engineer to help us make a difference to our planet.

As our Scientific Software Engineer, the job may be suitable for hybrid working, which is where an employee works part of the week in the office and part of the week from home.This is a voluntary, non-contractual arrangement and the location advertised will be your contractual place of work.

Our opportunity is full time, 37 hours per week. Our people are at the heart of what we do and we'll do our best toagreea working pattern that works for everyone.

World changing work

From science to technology, from meteorology to management, and from planning to communication, our expertise helps us stand out as the authority on weather accuracy and climate prediction. We help individuals, industries and government to make better decisions to stay safe and thrive. This is the Met Office. This is who we are.

• We’re aforcefor good - focusing on our environmental and social impact
• We’re experts by nature - always learning and developing to do things better
• We live and breathe it - putting our purpose at the heart ofdecision-making
• We’re bettertogether-understandingpartnerships and inclusivity make us greater
• We keep evolving - pushing boundaries to make tomorrow better for our customers

Your world of expertise

This role as a Scientific Software Engineer sits within the data-driven climate modelling project in the AI4Climate initiative at the Met Office Hadley Centre, where we are combining machine learning, deep learning data science, climate science, and high-performance computing to develop faster, more flexible approaches to climate predictions for downstream applications. We are looking for an exceptional SSE with strong data science and software engineering skills.

You will work at the intersection of AI and climate science, developing and explainable novel machine learning approaches for climate prediction and understanding how data-driven models (DDCMs) represent the Earth system. You will help advance scientific understanding of DDCMs and their role within future climate modelling systems.

You will join a multidisciplinary group of climate scientists, data scientists and software engineers, working closely with partners across the Met Office and internationally. You will help to join our pioneering work in DDCM as part of the Met Office AI4Climate initiative. This is your chance to apply cutting-edge Ml and Deep Learning AI to one of the most urgent challenges of our time-understanding and predicting Earth’s changing weather in warming climate in the Earth System Data Science team.

Your key duties:

• Develop and apply machine learning and deep learning methods for climate-focused tasks such as projection, prediction and emulation.
• Design, train and evaluate data-driven climate models using large-scale Earth system or simulated datasets.
• Investigate the scientific behaviour, robustness, uncertainty and physical realism of DDCMs.
• Develop new approaches for integrating physical understanding and machine learning methods.
• Design and implement evaluation frameworks for assessing model skill and scientific credibility.
• Contribute to research that advances understanding of Earth system processes through data-driven methods.
• Work collaboratively with climate scientists, software engineers and internal and external research partners.
• Contribute to the AI4Climate programme and wider Met Office strategy in data-driven modelling.
• Publish high-impact research, collaborate internationally and help shape the scientific direction of a rapidly emerging field.

Why join us

Our work is life-changing, often life-saving and always life-enhancing. The Met Office is Great Place to Work UK certified. We are also featured on their 'Best Workplaces in Tech' 2023, 2024 and 2025 lists, as well as their '54 Best Workplaces for Women' 2023 list.

As our Scientific Software Engineer, your total reward package will be up to £51,448 annually, which includes:

• £35,145 base pay
• An outstanding Civil Service pension, with an average employer contribution of 28.97%
• Recruitment Retention Allowance (RRA) you will be paid £2,000 per annum as a market supplement to reflect the demand for your skills. Whilst in post, you will be paid this marketdrivenallowance from April 2026 until March 2027 in your monthly pay
• Annual Leave starting at 27.5 days (plus Bank Holidays) rising to 32.5 days (plus Bank Holidays) after 5 years and option to buy or sell up to 5 days per year of annual leave

Essential Criteria, skills and experience:

• Lead Criteria: PhD, or equivalent knowledge and experience, in applying machine learning or deep learning to scientific, environmental or other complex datasets (Expert by Nature).
• Evidence of programming skills such as Python, ML-optimised data libraries and good quality assurance processes (Keep Evolving).
• Experience developing robust, maintainable and reproducible code in a scientific context.
• Ability to design experiments and evaluate methods to answer scientific questions.
• Understanding of statistical modelling, machine learning evaluation or uncertainty assessment.
• Experience working collaboratively in interdisciplinary teams (Better Together).
• Ability to communicate complex technical and scientific ideas clearly to both technical and non-technical audiences.

The panel may perform a preliminary sift of the lead criteria as indicated above.