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ML engineer
Machine learning engineers train models and put them into reliable software. Routes mirror software engineering with extra statistics and ML modules at university, then internships and graduate schemes. Use official job profiles for GCSE and degree requirements and the live board for schemes that are actually open.
Stages
- 1
GCSE choices
Strong maths and English. Computer science GCSE if available.
- 2
A-level or equivalent
Maths plus further maths, computer science or physics.
- 3
University or degree apprenticeship
Computer science, AI or data science. Some employers hire from physics and engineering with self-taught ML projects.
- 4
Work experience
Kaggle-style projects, open source contributions, or shadowing a data team.
- 5
Internships and insight
Data science or software internships with a modelling component.
- 6
Graduate schemes
Graduate schemes in technology, finance or retail with ML rotations.
- 7
First role
Junior ML engineer or data scientist in a product squad.
Entry requirements
Relevant degree or apprenticeship and demonstrable coding plus statistics.
National Careers ServiceCustom Path
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Questions
ML engineer vs data scientist?
ML engineers focus on production models and pipelines. Data scientists often focus on analysis and experimentation. Titles overlap in practice.
Where do entry requirements come from?
National Careers Service publishes the baseline for this role. Always confirm on the live page before you apply.
Does Navigait list every vacancy for this path?
No. We surface live posts from public employer boards. If a scheme is closed, the board stays empty rather than showing invented roles.