MLOps Engineer

Run the pipelines, monitoring and infrastructure that keep ML models healthy in production.

This UK mlops engineer career guide covers what the role involves day to day, typical salary at each stage, the usual entry route, the skills employers expect, and related careers worth comparing.

Quick facts

Starting salary
£50,000 - £70,000
Mid-career salary
£85,000 - £120,000
Senior salary
£140,000 - £200,000+
Work environment
Office or remote, desk-based
Time to entry
1 - 3 years
Degree required
Helpful, not always required
Category
AI, Data and Automation

What a MLOps Engineer does

Run the pipelines, monitoring and infrastructure that keep ML models healthy in production.

  • Training Infrastructure - Build GPU-cluster training pipelines.
  • Model Serving - Low-latency serving with vLLM, Triton or SageMaker.
  • Feature Stores and Pipelines - Build feature platforms and orchestration.
  • Model Monitoring - Drift, quality and cost monitoring for production models.

How to become a MLOps Engineer

  1. Look up MLOps Engineer roles on LinkedIn or Indeed and read 5 real job ads
  2. Talk to someone already working as a MLOps Engineer - even a 15-minute call helps
  3. Find one beginner course or qualification used by people in this role
  4. Build one small piece of evidence you've explored this (project, shadowing, short course)
  5. Apply to one entry-level role or related opportunity within the next month

Key skills

  • Docker/K8s
  • Cloud (AWS/GCP)
  • CI/CD
  • Monitoring
  • Python