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Machine Learning Engineer, Payments ML Accelerator

Stripe

New This Week
ML EngineeringPaymentsSenior (6-10 yrs)RemoteFintech Startup

Apply deep learning expertise to real-world payments challenges at one of the world's largest payment processors.

AI β†’ Finance

Location

Remote (US) / Seattle, WA

Salary Range

$212,000 – $318,000

Posted

Mar 27, 2026

Insider Signals

Beta
πŸ“ŠActive Hiring

Stripe has had 17 hiring events in the last 30 days β€” they're actively building.

Company AI Context

AI Maturity

cutting-edge

Tech Stack

pythonpytorchtensorflowlarge-scale-data-infra

Recent News

Stripe processes over $1T in payments annually and continues expanding ML-powered fraud and optimization capabilities.

Build deep learning models for fraud detection and authorization optimization on Stripe's payment platform, processing over $1T annually.

## About the Role The Payments ML Accelerator team at Stripe develops foundational ML capabilities that drive innovation across Stripe's payment products. You'll build deep learning models for fraud detection and authorization optimization. ## Responsibilities - Design and deploy deep learning architectures and foundation models across key payment entities - Identify high-impact opportunities and drive the long-term ML roadmap for payments - Architect generalizable ML workflows to enable rapid scaling - Develop advanced ML solutions spanning the full lifecycle from research to production - Partner with product and engineering teams ## Requirements - Strong background in machine learning and deep learning - Experience building and deploying models at scale - Proficiency in Python and ML frameworks (PyTorch, TensorFlow) - Strong technical judgment

Skills & Technologies

Deep learningFoundation modelsFraud detectionPayment optimizationPythonPyTorchTensorFlowML infrastructure

Best Backgrounds

  • ML engineer
  • applied scientist
  • deep learning researcher
  • fraud ML engineer

Related Titles to Explore

  • Senior ML Engineer, Fraud
  • Staff Data Scientist, Payments
  • Applied Scientist, Payment Risk
  • ML Platform Engineer

Career Bridge Playbook

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Career paths into this role

ML engineer
applied scientist
research scientist
deep learning engineer

Where this role leads

Staff ML Engineer, Payments
Head of ML, Fraud Detection
Principal Scientist, FinTech
VP of AI, Payments

Transition Difficulty

medium

Key Skill Gaps to Close

  • payment domain knowledge
  • fraud pattern recognition
  • real-time serving at scale

Skills used in this role

Technical

deep-learningfoundation-modelsfraud-detection-mlpayment-optimizationpythonpytorchtensorflowml-infrastructurereal-time-inference

Domain

payment-systemsfraud-preventionauthorization-optimizationfinancial-transactions

Soft Skills

cross-functional-collaborationtechnical-leadershipresearch-to-production

Interested in this role?

Apply directly on the company's career page.

Apply Now

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