Machine Learning Engineer, Link

Stripe
New York
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 6+ yearsSkills: ["Collaboration","Problem ownership","Data-driven decision-making","Judgment","Cross-functional partnership"]

Build and operate machine learning models and risk decisioning systems for Link Fraud and Auth. Own the full ML lifecycle—analyzing fraud patterns, developing features and experiments, and deploying models into production with monitoring and iteration. Partner with Engineering, Product, Data Science, and Risk to improve fraud performance, authorization rates, and Link’s ability to expand into new payment experiences.

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FursaFursa
Stripe
Stripe
16 hours ago

Machine Learning Engineer, Link

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 12 hours agoStatus: Live

Job Summary

Build and operate machine learning models and risk decisioning systems for Link Fraud and Auth. Own the full ML lifecycle—analyzing fraud patterns, developing features and experiments, and deploying models into production with monitoring and iteration. Partner with Engineering, Product, Data Science, and Risk to improve fraud performance, authorization rates, and Link’s ability to expand into new payment experiences.
Location: New York
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build, train, evaluate, deploy, and own ML models that detect fraud and abuse across Link.
  • •Use large-scale datasets to investigate emerging threats, develop hypotheses, and improve payment performance.
  • •Develop pragmatic ML solutions, including tree-based models, for real-time risk decisioning.
  • •Design data pipelines, features, evaluation methods, experiments, and monitoring systems for reliable production models.
  • •Own ambiguous problems from analysis through technical design, implementation, launch, measurement, and iteration; collaborate cross-functionally to deliver durable outcomes.

Key Requirements

  • •6+ years of industry experience building and shipping machine learning models in production.
  • •Strong programming skills in Python and experience with data/ML tools such as SQL, Spark, and XGBoost.
  • •Strong knowledge of production ML systems (data pipelines, feature development, evaluation, deployment, monitoring, and iteration).
  • •Experience working with large, complex datasets and applying data analysis, statistics, and experimentation fundamentals.
  • •Demonstrated ability to take an open-ended business problem, determine where ML helps, and own the solution through production.
Experience:6+ yearsFraud detectionRisk modelingPaymentsFintechDigital wallets
Skills:CollaborationProblem ownershipData-driven decision-makingJudgmentCross-functional partnership
Languages:English
Tech Stack:PythonSQLSparkXGBoost

Company Brief

Stripe
Provides payment processing APIs and financial infrastructure for internet businesses. Powers online payments for millions of companies from startups to Fortune 500s.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Decacorn (USD 10B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2010
Glassdoor
Glassdoor: 4.2
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