Senior Machine Learning Engineer - Fraud

Plaid
San Francisco, Seattle, New York
Workplace: HybridFull timeUSD 228,960 - 315,360 annuallyFunction: Data Science & Machine LearningSkills: ["Ownership","Problem-solving","Cross-functional collaboration","Independent leadership"]

Develop and deploy fraud detection models for Plaid’s Fraud Data team, from discovering signals and experimenting with features to production deployment and ongoing optimization. Build training datasets and predictive features, design experiments using agreed detection and false-positive metrics, and partner with engineering to balance quality, latency, cost, and reliability. Independently lead ML projects and explore using LLMs and Generative AI to improve fraud prevention and investigation.

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Plaid
Plaid
2 hours ago

Senior Machine Learning Engineer - Fraud

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Last checked: 1 hour agoStatus: Live

Job Summary

Develop and deploy fraud detection models for Plaid’s Fraud Data team, from discovering signals and experimenting with features to production deployment and ongoing optimization. Build training datasets and predictive features, design experiments using agreed detection and false-positive metrics, and partner with engineering to balance quality, latency, cost, and reliability. Independently lead ML projects and explore using LLMs and Generative AI to improve fraud prevention and investigation.
Location: San Francisco, Seattle, New York
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Investigate fraud patterns and model errors to identify new signals and improve detection coverage.
  • •Develop training datasets and predictive features, addressing issues such as incomplete labels, class imbalance, data leakage, and changing fraud behavior.
  • •Design, train, tune, and evaluate traditional and modern ML models, including experiments comparing architectures.
  • •Build data and training pipelines that enable reproducible experiments and efficient iteration on features and models.
  • •Deploy models with engineering and ML infrastructure partners, balancing detection quality, latency, cost, and reliability, and independently lead ML projects through release.

Pay and Benefits

Salary: USD 228,960 - 315,360 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVision401k

Key Requirements

  • •7+ years of professional experience in machine learning, applied science, or software engineering for ML, including hands-on model development and deployment.
  • •Hands-on experience designing, training, tuning, and deploying models, measuring improvements in production performance or business metrics.
  • •Strong ML and statistical fundamentals, including feature engineering, experiment design, model evaluation, and diagnosing underperformance.
  • •Experience constructing training datasets and addressing label quality, data leakage, class imbalance, and generalization across time periods or populations.
  • •Strong Python skills and SQL proficiency, with hands-on experience using ML frameworks such as PyTorch, scikit-learn, or XGBoost (or equivalents).
Experience:Fraud/risk modeling
Skills:OwnershipProblem-solvingCross-functional collaborationIndependent leadership
Tech Stack:PythonSQLPyTorchScikit-learnXGBoostGradient-boosted treesNeural networksLLMsGenerative AITransformersFoundation modelsGraph-based systemsModel deploymentFeature engineering

Company Brief

Plaid
Provides APIs that enable applications to connect with users’ bank accounts, verify financial data, and power payment and account verification workflows for fintechs and financial services companies.
Industry: Fintech Infrastructure
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series D
Headquarters: San Francisco, United States
Founded: 2013
WebsiteLinkedIn