DevOps Engineer - AI Operations at Met Office
Exeter EX1 3PB, , United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

09 Aug, 25

Salary

2200.0

Posted On

10 May, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Research, Architects, Artificial Intelligence, Operations, Infrastructure, Scientific Programming, New Opportunities, Government, Features, Python, Meteorology, Decision Making, Boundaries, Forecasting, Technology, Cloud Computing, Social Impact

Industry

Information Technology/IT

Description

Job Introduction
We’re looking for two exceptional DevOps Engineer to help us make a difference to our planet.
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.

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)
Responsibilities
  • 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
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