Machine Learning Platform Engineer
Monzo - Cardiff, London or Remote (UK); London
Posted Jul 31, 2025
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Machine Learning Platform Engineer Cardiff, London or Remote (UK); London 🚀 We're on a mission to make money work for everyone. We're waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts , accounts for 16-17 year olds , a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save , invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We're not about selling products - we want to solve problems and change lives through Monzo ❤️ 📍London / UK Remote | £78,000 - £110,000 + Incentive Awards tied to your performance + Benefits About Machine Learning Platform Engineering at Monzo: The Platform Collective builds and maintains the infrastructure, tools and processes that sets the rest of Monzo technology teams up for success. We work on a wide range of shared infrastructure, services and engineer tooling. The Machine Learning Platform team sits within the Platform Collective and is responsible for designing, building, and maintaining the infrastructure and tools which empower our teams to train, evaluate, deploy, and serve Machine Learning models and features
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