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Machine Learning Ops Engineer

Access Computer Consulting
Posted 13 hours ago, valid for 10 days
Location

Ilford, Greater London IG1 2AH, England

Salary

£500 - £550 per day

Contract type

Full Time

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Sonic Summary

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  • I am recruiting for a Machine Learning Ops Engineer to work on a hybrid basis, spending 2 days a week in North Greenwich and 3 days remote.
  • The role falls inside IR35, requiring candidates to work through an umbrella company for the duration of the contract.
  • Candidates must have technical experience as a Machine Learning Ops Engineer, with a minimum of 3 years of relevant experience.
  • Experience in implementing ML models using the Azure stack, as well as proficiency in Python and Scala, is essential for this position.
  • The salary for this role is competitive and will be discussed during the application process.

I am recruiting for a Machine Learning Ops Engineer to work on a hybrid basis - 2 days a week in North Greenwich, 3 days remote.

The role falls inside IR35 so you will need to work through an umbrella company for the duration of the contract.

You must have technical experience as a Machine Learning Ops Engineer.

As the Machine Leaning Ops Engineer you will have worked on numerous projects of a large scale and size.

Experience of implementing ML models using the Azure stack is essential.

You must also have experience in Python and Scala in relation to ML models.

You will be accountable and responsible for understanding the requirements, ensuring the model is built to production standards, looking at how the model can be deployed, as well as streamlining the processes, automating those processes, and ensuring that the client is using the right tools correctly.

Initially you will be responsible for reviewing the D&A Data Science proof of concept. You will need to understand through the D&A Product Owner the requirements and what the output needs to look like. You will then ensure that the model has been developed in a manner that ports to a production environment and will provide feedback and guidance on any model changes that would be needed to optimise for production deployments.

If this role is of interest please apply ASAP to find out more!

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