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Machine Learning Engineer

DevOps engineers build and look after the computer systems that companies use to make and deliver software. They automate boring tasks, make sure servers run smoothly, and help developers get new features out to people as quickly and safely as possible.

Machine Learning Engineer

28

Engineering and Technology

AI IMPACT
AI CAN DO28%moving to73%
THE DOOR, NOWB
THE DOOR, 20 YRSD
STARTING PAY£30,000 - £40,000
NO MOATNo physical, legal or personal barrier protects this work from software.
AI helps here, but has not taken over
AI can already do some of this job, but the day-to-day work still leans on a person to decide, check and take responsibility. Nothing formally protects this job though, so the safest move is to keep building the judgement AI cannot yet copy.

The role

As a DevOps engineer, you work between software developers and the IT operations teams. You build the systems that let developers write code, test it, and push it live without things breaking. You use tools and automation to make this whole process faster and more reliable - so instead of manually checking everything by hand, machines do the checking for you.

Your days mix different kinds of work: you might be writing automation code, checking that servers are running well, fixing problems when something goes wrong, or working with cloud platforms like Amazon Web Services to keep everything running smoothly. You think about security and make sure that sensitive data stays safe. It is technical and hands-on work that needs you to understand both how software is built and how to run the computers it runs on.

Daily responsibilities

  • Collaborate with software developers and IT staff to oversee code releases.
  • Implement automation tools and frameworks (CI/CD pipelines) to streamline operations.
  • Monitor system performance, troubleshoot issues, and ensure high availability of services.
  • Manage cloud infrastructure and services, optimizing for cost and performance.
  • Maintain security protocols and compliance standards across all deployments.
  • Conduct regular system tests and updates to ensure reliability and security.
  • Document processes and create runbooks for operational procedures.

Does a degree help here?

A UK degree, particularly in Mathematical Sciences or Computer Science, provides a robust foundation in analytical thinking and problem-solving. UK universities are renowned for their rigorous curricula and strong industry connections, giving graduates a competitive edge in the job market.

Careermash

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AI EXPOSURE = the share of a job's day-to-day tasks AI can already do today, from the same exposure engine used across this site (Anthropic labour market research, 2026, observed real-world AI usage by occupation). Higher means more exposed. It is a measurement of now, not a prediction. THE DOOR = how hard the job is to get into, grade A (easy) to E (extremely hard), from each career's published forecast (OpenAI, "The AI Jobs Transition Framework", Richmond 2026, CC BY 4.0). A card marked MOAT NOT YET CLASSIFIED has a real exposure score but no entry yet in our moat register, so we make no claim about what structurally protects it. Scorecard grades and verdicts are Careermash editorial judgment: we show forecasts as forecasts and own our conclusions. Salary and pathway figures are each career's own published profile. Careermash is a service provided by What School Ltd.

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