Machine Learning Engineer - Apprentice

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Would you like to be a part of a digital transformation journey and be part of a team that is constantly evolving? Do you want to be involved in work that has a meaningful purpose? If yes, then this could be the role for you!

Job Summary

As an Apprentice Machine Learning Engineer youll be focused on developing a foundational understanding of the Machine Learning (ML) life cycle. An essential part of the team, you will support your colleagues in delivering effective, secure, and sustainable ML models, while focusing on learning the fundamentals of the technical infrastructure required to design, train, deploy, and scale these models in products and services.

Apprenticeship Detail

An Apprenticeship provides work-based, on the job training and development. The training is fully funded so it does not cost you anything and you will earn whilst you learn. They provide you with the skills, knowledge and behaviours you need to be fully effective in a designated role. Therefore, with very few exceptions, you do not need to have related work experience/ qualifications to apply.

Whats important throughout the Apprenticeship is that you put into practice what you learn, and capture evidence of this so your progress and increasing capability can be assessed.

We want you to get the most out of your Apprenticeship. To help you manage your learning well give you over the duration of the Apprenticeship, a minimum of 20% of your paid working hours to focus on skills development. This means you wont be asked to study in your own time. However, both the role and the Apprenticeship are very demanding and youll need to work hard.

You will be assessed throughout and at the end of your Apprenticeship by submitting coursework and End-point assessment.

There is plenty of support and youll be part of a larger apprentice community and where possible well get you involved in apprenticeship related activities, so youll get to know people outside of your own team or Department.

Further information can be found in the apprenticeship standard for this Apprenticeship Standard you should read this to see the skills, knowledge and behaviours you will need to have learned by the end of your apprenticeship:

https://skillsengland.education.gov.uk/apprenticeships/st1398-v1-0

There you can also find a link to the assessment plan. This will give you details of how the apprenticeship is assessed.

Acceptable qualifications include any of:

• Two A-levels in one or more similar subject plus B in A-Level maths.

• Two A-levels in one or more similar subject plus 2-years work experience in tech.

• Level 4 or 5 apprenticeship in a similar technical subject.

• International Baccalaureate at Level 3 in a similar subject.

• 3+ years in a similar subject-related role.

• A first degree in a numerate discipline (but excluding Computer Science as not fundable)

You may also have a combination of qualifications and experience which demonstrate the minimum foundation needed for the programme. In this instance you could still be considered for the programme.

If you hold international equivalents of the above qualifications, at the time of your application you must be able to provide an official document that states how your international qualifications compare to the UK qualifications. For more information please visit the UK ENIC website.

Please Note:

• If you dont meet the above apprenticeship criteria we cannot progress your application for this role.

• If you are not sure whether or not you meet the criteria please contact [email protected]

Key Accountabilities:

• Design, prototype, and test machine learning models.

• Run experiments to improve performance of AI systems and large language models.

• Help build and manage tools for evaluating and deploying AI solutions.

• Monitor and support production AI systems to ensure they run smoothly.

• Work with teams across the business to align AI projects with real-world goals.

• Stay up to date with AI trends and contribute fresh ideas.

Essential Criteria (to be assessed at application stage):

• Some experience or knowledge in software, data, or tech-related fields.

• Python skills and interest in machine learning tools and frameworks.

• Curious about large language models (LLMs), prompt engineering, or AI evaluation.

• Eager to learn and grow in a fast-paced tech role.

• Passionate about AI, data, and innovation.