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136,000+ live jobsHybrid in London·Full-time·Added 19 days ago (last checked 9 Oct)
£135,000 - £175,000 a year
Gross, as stated in the ad.
About £6,940 - £8,710 a month after tax.
Full-time
Per the ad.
Hybrid
Office and home days — the ad has the split.
Be near London for hybrid days
No relocation package mentioned.
Have senior-level experience
Lead-level role.
Nice to have
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Wise is a global technology company, building the best way to move and manage the world's money.
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.
More about our mission and what we offer.
Wise protects millions of customers and billions in transactions from fraud, money laundering and financial crime. Our ML systems are the front line of defense - operating at a global scale of 100K requests/minute under strict sub-50ms latency SLAs. We need an exceptional technical leader to own how these models are engineered, shipped and scaled.
We're hiring a Senior ML Engineering Lead to build and grow Wise's Risk Modelling engineering pillar. You will own the full model lifecycle standard for financial crime detection - from offline experimentation to production deployment and real-time monitoring and build the team to execute it. Your job is to build the automated engineering ecosystem and organisation that scales this safely to hundreds of models.
This is a rare greenfield leadership role with strong investment and engagement from Wise's CTO and senior leadership.
Risk ML sits within Wise's FinCrime organisation, owning the full ML and AI foundation for financial crime detection. We're have three dedicated pillars - Feature Platform, Learning Loop and Risk Modelling. You'll lead the Risk Modelling pillar, leading a team of Senior ML Systems Engineers and Applied ML Engineers.
We operate with high autonomy and low hierarchy. You'll own the engineering strategy end-to-end - from architecture decisions and infrastructure design through to hiring, team culture and cross-platform partnerships. We value leaders who shape direction and build teams, not just manage delivery.
The Model Factory: Architect the declarative pipeline that turns a configuration file into a deployed, monitored model - the engineering backbone for scaling to hundreds of models
The Experimentation Engine: Establish the reusable path from research (partnering with DS Research) to high-throughput production for traditional and modern architectures
Model Operations: Build the infrastructure for automated retraining, drift detection, threshold simulation/management and audit trails - the operational layer required to run hundreds of models safely at scale
The Team: Recruit, lead and mentor a world-class team of ML engineers. Establish a high-performance, engineering-first culture from scratch - setting hiring standards, technical bar and growth paths
Cross-Platform Partnership: Define and navigate the partnership with key platform teams - owning the build vs consume decisions for your pillar
You've explicitly led or built an ML Engineering or model lifecycle automation team (not just used one) at a high-growth company - you defined the standards that other engineering teams followed
System-level and mathematical depth: you can design a model factory architecture, review a training pipeline & debug a runtime inference latency regression
Experience in high-throughput environments where latency constraints are tight and model failures carry massive financial consequences
Track record of hiring and developing senior engineers - you've built a team, not just inherited one
Ability to navigate ambiguity and make architecture-level decisions with incomplete information - this is a greenfield build, not an optimisation role
Strong enough technically to guide and review across deep learning, ML systems and production infrastructure - you lead through depth, not just delegation
Experience at a tier-1 fintech or payments company
Experience with graph-based methods (GNNs, entity resolution) in production
Foundation model fine-tuning or LLM evaluation experience
Experience establishing ML engineering practices in organisations transitioning from classical ML to deep learning
Wise Engineering - https://medium.com/wise-engineering
Starting salary: £135,000 - £175,000 + RSUs
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Recruiter conversation
With a recruiter · Phone call
Phone conversation about your experience, motivations and knowledge of Wise; the recruiter explains the role and next steps.
Technical test
Not every role
Depending on the role: a case study, take-home challenge or technical test; software engineers do a paired coding exercise.
Meet the team
With a team members and your Lead · Video call
Open-ended and scenario-based questions with the team you would join and your Lead, including a values-fit assessment.
Offer
or browse London·Engineering·Machine learning & AI·Senior·Hybrid·Banking & Fintech·Fintech
We're looking for an Engineering Lead to join the Account Management team. This team is building the Current Account and Everyday banking experience products, which sit at the heart of Wise.
We are looking for mission-driven senior product engineers to join our Grow squad.
Wise moves billions across borders every year. Behind every transaction is a decision: is this safe? Our ML systems make that call - at scale, in real time, across every market we operate in.
Wise is a global technology company building the best way to move and manage the world’s money: min fees, max ease, full speed.
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