Role details
Company Description
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 .
Job Description
About the role
- 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.
How we work:
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.
What will you be working on?:
What do you need?:
- 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
Nice to Have
- 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
Interested? Find out more:
- How we work – a practical guide
- DEI @ Wise
- Wise Tech Stack (2025 update)
- See what it's like to work at Wise London!
- Our Engineering career map
- Wise Engineering – https://medium.com/wise-engineering
What do we offer:
- Starting
- Wise Benefits
#LI-AB3 #LI-Hybrid
Additional Information
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 .