Senior ML Platform Engineer I - Financial Crime

Wise
London
Workplace: HybridFull timeGBP 87,500 - 111,000 annuallyFunction: DevOps, Cloud & InfrastructureSkills: ["Product mindset","Building for adoption","Collaboration","Reliability","Systems thinking"]

Build Wise’s Risk ML model lifecycle platform for financial crime detection, turning bespoke workflows into a scalable, standardized pipeline. Own declarative training, model packaging and serving abstractions, evaluation frameworks, and monitoring with drift detection and audit trails for regulatory compliance. Partner with data scientists, feature platform engineers, and the central ML platform team to integrate FinCrime lifecycle tooling on shared infrastructure and maximize data science productivity.

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FursaFursa
Wise
Wise
21 hours ago

Senior ML Platform Engineer I - Financial Crime

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

Job Summary

Build Wise’s Risk ML model lifecycle platform for financial crime detection, turning bespoke workflows into a scalable, standardized pipeline. Own declarative training, model packaging and serving abstractions, evaluation frameworks, and monitoring with drift detection and audit trails for regulatory compliance. Partner with data scientists, feature platform engineers, and the central ML platform team to integrate FinCrime lifecycle tooling on shared infrastructure and maximize data science productivity.
Location: London
Workplace: Hybrid
Employment Type: Full time · Permanent
Job Function: DevOps, Cloud & Infrastructure
Seniority: Mid level

Key Responsibilities

  • •Design and build a declarative, config-driven training pipeline that standardizes model training.
  • •Create model packaging and serving abstractions with a consistent API across model types.
  • •Implement a model evaluation framework with standardized metrics and reproducible comparisons and validation gates.
  • •Build model monitoring including drift detection, performance degradation alerts, retraining triggers, and audit trails.
  • •Own the integration layer between FinCrime lifecycle tooling and Wise’s central ML infrastructure.

Pay and Benefits

Salary: GBP 87,500 - 111,000 annually
Equity and Bonus:Equity

Key Requirements

  • •Experience building ML platform infrastructure in production (training pipelines, model serving, evaluation frameworks, or monitoring systems).
  • •Strong software engineering fundamentals with Python, Kotlin/Java, and SQL.
  • •Experience with ML orchestration tools (Airflow, Kubeflow, or equivalent), model registries (MLflow or similar), and container-based deployment.
  • •End-to-end understanding of the ML lifecycle from data ingestion through training, packaging, serving, and monitoring.
  • •Product mindset for internal tooling—build for adoption and internal users, not just functionality.
Experience:Financial servicesFinancial crimeFinTechFraudAMLRegulated environments
Skills:Product mindsetBuilding for adoptionCollaborationReliabilitySystems thinking
Languages:English (UK)
Tech Stack:PythonKotlin/JavaSQLAirflowKubeflowMLflowONNXAPIDeclarative training pipelineModel servingModel monitoringDrift detectionAudit trails

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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