As our DevOps 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 to agree a 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 a force for 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 of decision-making
We’re better together - understanding partnerships and inclusivity make us greater
We keep evolving - pushing boundaries to make tomorrow better for our customers
Job description
Your world of expertise
Artificial Intelligence (AI) is creating new, transformative, ways to deliver weather and climate science and services. It has the potential to reduce compute requirements thousands-fold compared to existing numerical weather prediction (NWP) methods, opening new opportunities such as high-resolution “km-scale” prediction, and moving forecasting out of the domain of supercomputers and onto edge devices. To realise any of these opportunities as an operational service that delivers customer value, the Met Office needs the capability to develop and run data-driven workflows in a secure, sustainable and cost-effective way. There is a strong need for a consistent AI Operations Platform that enables internal users to do foundation AI research, develop valuable datasets, and then rapidly pull-through to operations data-driven weather and climate services. In this post you will be a core developer of the AI Operations platform, implementing features to ensure it is suitable for Met Office weather and climate workloads and that deploying AI models into operations is repeatable, scalable and highly available.
Your key duties:
The DevOps engineer (GDaD DevOps role) for AI Operation’s key responsibilities will be to:
Develop the AI Operations Platform to meet the requirements of research, development and operational AI workloads at the Met Office.
Apply modern development standards, such as MLOps, infrastructure-as-code, and CI/CD, and support users of the service to adopt complementary processes.
Build, maintain and support key AI/ML development toolchains suitable for a wide range of Met Office data science applications.
Work collaboratively with users, architects and other stakeholders to refine specifications and develop prototype new services.
Person specification
Essential Criteria, skills and experience:
Experience developing software and/or automation scripts in Python. (Experts by Nature)
Understanding of modern agile DevOps workflows.
Ability to work effectively within a multidisciplinary team. (Better Together)
Experience or a demonstrable desire to learn and apply new tools and techniques, specifically in some of the areas of scientific programming, machine learning operations (“MLOps”), automation, and cloud computing. (We keep evolving)
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