Senior ML Engineering Lead - Financial Crime

Wise
London
Workplace: HybridFull timeGBP 135,000 - 175,000 annuallyFunction: Data Science & Machine LearningSkills: ["Leadership","Team building","Mentoring","Cross-platform partnership","Decision-making"]

Own the full lifecycle engineering for financial crime detection ML models, from offline experimentation to real-time production monitoring. Lead a greenfield Risk Modelling engineering pillar inside Wise’s FinCrime organization, building the automated model factory, experimentation engine, and model operations for safe scaling to hundreds of models. Recruit and mentor senior ML systems and applied ML engineers, define engineering strategy, and partner cross-platform to make build-vs-consume decisions.

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FursaFursa
Wise
Wise
11 hours ago

Senior ML Engineering Lead - Financial Crime

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Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

Own the full lifecycle engineering for financial crime detection ML models, from offline experimentation to real-time production monitoring. Lead a greenfield Risk Modelling engineering pillar inside Wise’s FinCrime organization, building the automated model factory, experimentation engine, and model operations for safe scaling to hundreds of models. Recruit and mentor senior ML systems and applied ML engineers, define engineering strategy, and partner cross-platform to make build-vs-consume decisions.
Location: London
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Manager level

Key Responsibilities

  • •Own how financial crime detection ML models are engineered, shipped, scaled, and monitored from experimentation through production.
  • •Architect the “Model Factory” declarative pipeline that turns configuration into deployed, monitored models at scale.
  • •Establish the “Experimentation Engine” path from research to high-throughput production for traditional and modern architectures.
  • •Build “Model Operations” infrastructure for automated retraining, drift detection, threshold simulation/management, and audit trails.
  • •Recruit, lead, and mentor the Risk Modelling team and define engineering strategy end-to-end, including hiring standards and cross-platform build/consume decisions.

Pay and Benefits

Salary: GBP 135,000 - 175,000 annually
Equity and Bonus:Equity

Key Requirements

  • •Have explicitly led or built an ML engineering or model lifecycle automation team at a high-growth company, defining standards others follow.
  • •Design model factory architectures and deeply understand training pipelines and runtime inference latency/debugging.
  • •Experience in high-throughput environments with tight latency constraints and high financial impact from model failures.
  • •Have a track record hiring and developing senior engineers, building teams (not inheriting one).
  • •Navigate ambiguity to make architecture-level decisions in a greenfield build, with the depth to guide across ML systems and production infrastructure.
Experience:Financial servicesFintechPayments
Skills:LeadershipTeam buildingMentoringCross-platform partnershipDecision-making
Languages:English (UK)
Tech Stack:Machine learningML systemsModel lifecycleModel deploymentReal-time monitoringDrift detectionLatencyProduction inferenceDeep learningGraph neural networksEntity resolutionLLM evaluationModel retraining

Company Brief

Wise
Wise (formerly TransferWise) is a London-based fintech that provides low-cost international money transfers, multi-currency accounts and payment infrastructure for individuals and businesses worldwide.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: London, United Kingdom
Founded: 2011
Glassdoor
Glassdoor: 3.8
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