Senior Machine Learning Engineer I - FinCrime

Wise
London
Workplace: HybridFull timeGBP 87,500 - 111,000 annuallyFunction: Data Science & Machine LearningEducation: bachelorsSkills: []

Build and scale the integrity layer of the label platform that powers Risk ML models, focusing on label quality, monitoring, and statistical integrity. Design automated audit processes to evaluate label quality over time, and own end-to-end work across model training, evaluation, and pipeline deployment. Collaborate with cross-functional partners across Risk Intelligence, Data Engineering, and Product to ensure ML learns from clean, reliable data.

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FursaFursa
Wise
Wise
4 days ago

Senior Machine Learning Engineer I - FinCrime

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Last checked: 14 hours agoStatus: Live

Job Summary

Build and scale the integrity layer of the label platform that powers Risk ML models, focusing on label quality, monitoring, and statistical integrity. Design automated audit processes to evaluate label quality over time, and own end-to-end work across model training, evaluation, and pipeline deployment. Collaborate with cross-functional partners across Risk Intelligence, Data Engineering, and Product to ensure ML learns from clean, reliable data.
Location: London
Workplace: Hybrid
Employment Type: Full time · Permanent
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build, scale, and maintain the integrity layer of the label platform for Risk ML models.
  • •Define, implement, and monitor statistical fundamentals and key quality metrics for data and labels.
  • •Design automated audit processes to evaluate and monitor label quality over time.
  • •Work end-to-end on machine learning model training, evaluation, and pipeline deployment.
  • •Collaborate with cross-functional partners across Risk Intelligence, Data Engineering, and Product.

Pay and Benefits

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

Key Requirements

  • •Degree in STEM (Computer Science, Mathematics, Statistics, Physics, Chemistry, Electrical Engineering, or a related quantitative field).
  • •Strong mathematical and statistical fundamentals with experience applying statistical analysis to complex data.
  • •Hands-on experience across the machine learning lifecycle, including training, evaluation, and deployment, using ML/AI and techniques such as neural networks or NLP.
  • •Strong proficiency in Python or Java for data scripting and production engineering, plus advanced SQL capability.
  • •Hands-on experience building static data pipelines, performing deep-dive data analysis, and using data visualization tools to understand statistical behavior.
Experience:FintechE-commerceFast-scaling techCompetitive machine learningKaggleOpen sourceDeveloper tools
Education:Bachelor's in STEM (Computer Science, Mathematics, Statistics, Physics, Chemistry, Electrical Engineering, or related quantitative field)
Languages:English
Tech Stack:PythonJavaSQLKafkaMachine LearningAINeural NetworksNLPGraph Neural NetworksGNNSupport Vector MachinesSVMTransformersLSTMsData visualization

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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