Senior ML Engineering Lead Financial Crime

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.

Were hiring a Senior ML Engineering Lead to build and grow Wises 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 Wises CTO and senior leadership.

How we work:

Risk ML sits within Wises FinCrime organisation owning the full ML and AI foundation for financial crime detection. Were have three dedicated pillars - Feature Platform Learning Loop and Risk Modelling. Youll 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. Youll 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:

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

What do you need:

Youve 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 - youve 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 its like to work at Wise London!

• Our Engineering career map

• Wise Engineering do we offer: 

  • Starting salary: 135000 - 175000 RSUs

  • Wise Benefits

  #LI-AB3 #LI-Hybrid

   

  
  

  Additional Information :

  For everyone everywhere. Were people building money without borders  without judgement or prejudice too. We believe teams are strongest when they are diverse equitable and inclusive.

  Were 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 its like to work at Wise visit .

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  Remote Work :

  No

  
  

  Employment Type :

  Full-time