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AI Trade-Based Money Laundering Detector

Jordan Lindqvist

Full-time · Job · New_York

About the role

Trade-based money laundering — manipulating international trade invoices to move value across borders — is estimated to account for $1.6 trillion in illicit flows annually. It is also among the hardest financial crimes to detect because it requires correlating customs data, shipping records, commodity pricing databases, and correspondent banking flows across different jurisdictions. We build financial crime analytics for tier-1 banks and customs authorities. Our TBML detection system processes 40 million trade transactions per month, cross-referencing invoice values against fair market price ranges, flagging unusual counterparty relationships, and identifying the circular trade patterns characteristic of value transfer schemes. You will lead detection model development: designing features from heterogeneous data sources, building the graph models that identify suspicious trade relationship networks, and developing the alert scoring that meets the precision requirements of compliance teams who cannot afford to investigate thousands of false positives per day.

Responsibilities

  • Design multi-source features combining customs data, shipping records, and banking flows
  • Build graph models detecting circular trade patterns and suspicious counterparty networks
  • Implement commodity price deviation scoring against fair market benchmarks
  • Develop alert precision optimization meeting compliance investigation capacity constraints
  • Validate detection models against confirmed TBML case histories
  • Collaborate with financial crime compliance experts on typology encoding

Requirements

  • 6+ years in ML engineering with financial crime, trade finance, or compliance domain experience
  • Experience with graph-based features and network analysis for anomaly detection
  • Strong Python, PyTorch, and Spark skills for large-scale transaction data
  • Understanding of international trade finance, customs processes, and AML regulations
  • Track record building high-precision detection models for compliance-constrained environments

Benefits

  • Fully remote
  • Top-of-market compensation
  • Health, dental, and vision
  • $5,000 annual compliance certification and conference budget
  • Equity package

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch spark sql statistics

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch spark sql statistics docker

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