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Hire machine learning engineers in the UK

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

What you will pay

£48k to £160k, most around £83k

The range employers advertised for machine learning engineers on Artificial Intelligence Jobs over the last 12 months, base salary only, across 88 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 machine learning engineers on Artificial Intelligence Jobs right now

  • Anthropic 2
  • ECM Selection 1

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

PhysicsX

Senior Machine Learning Engineer

  • London
  • Hybrid · 3 days in office
  • Senior

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, forecasting, anomaly detection) into customer production environments, building scalable training and inference pipelines with Python, PyTorch and Kubeflow. Leads architecture and scoping with customers, mentors engineers, and travels to client sites 3-4 weeks per quarter.

PyTorch · Pandas · FastAPI +2

Yesterday

PhysicsX

Senior Machine Learning Engineer

  • New York, United States
  • Hybrid
  • US$200,000 – US$250,000 pa
  • Senior

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments, using Python, PyTorch, Pandas, fastAPI, Scipy and Kubeflow across cloud and on-prem. Leads scoping and architecture for data/ML systems, mentors engineers, and travels to customer sites roughly 3-4 weeks per quarter.

Python · PyTorch · Pandas +3

Yesterday

PhysicsX

Principal Machine Learning Engineer

  • Singapore
  • Lead

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments. Leads scoping and architecture for data/ML systems, builds training and inference pipelines and APIs on cloud and on-prem, and mentors engineers while travelling to customer sites 3-4 weeks per quarter.

Python · PyTorch · Pandas +3

Yesterday

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