Hire by role

Hire mlops engineers in the UK

What mlops engineers are paid, what to name in the advert, and who you are up against — from the adverts on Machine Learning Jobs, not a survey. Looking for the roles themselves? See MLOps Engineer jobs.

What you will pay

£35k to £108k, most around £88k

The range employers advertised for mlops engineers on Machine Learning Jobs over the last 12 months, base salary only, across 7 priced adverts. Adverts that state a salary get more applications than those that hide it, and a figure at or above the midpoint is the single cheapest thing you can do for the response.

Remote or anchored

A fully remote role draws the whole country and can pay a little under the London figure; an anchored one competes locally and cannot.
Greenfield or inherited

Building from nothing is worth more to the right person than running what exists, and they will ask which it is.
Someone senior to learn from

A strong lead in the team is worth thousands on the offer; without one, expect to pay for that experience directly.

Who you are competing with

Hiring mlops engineers on Machine Learning Jobs right now

Three live adverts for the role, as candidates see them. How rivals pitch it is worth a look before you write yours.

Harnham - Data and Analytics Recruitment

MLOps Engineer

London
Hybrid
£75,000 – £95,000 pa
Senior

Own and develop the MLOps infrastructure behind a growing AI platform, building orchestration pipelines with Dagster, Airflow or Prefect and deploying ML workloads on Kubernetes and cloud. You will implement CI/CD, observability and monitoring, manage infrastructure as code with Terraform or Bicep, and work closely with Data Scientists and ML Engineers to scale production ML, NLP and AI systems.

Dagster · Airflow · Prefect +3

3 days ago

Adria Solutions

Junior DevOps / MLOps Engineer

Huddersfield
Hybrid
£35,000 – £45,000 pa
Junior

Supports AWS infrastructure, CI/CD pipelines and automation for software and machine learning workloads, including packaging, versioning and deploying ML models. Works with software and AI engineers to keep development, testing and production environments consistent, monitoring pipelines and fixing issues. Suits an early-career engineer with cloud, scripting and Git foundations.

AWS · GitHub · GitHub Actions +5

Last month