Machine Learning Engineer Ii (fraud)

Affirm

Remote, US
Base: $125,000 - $175,000 py; equity: eligible for...
Remote
2+ years ml engineering experience
Python production-quality code
Tabular classification models
Affirm is seeking a Machine Learning Engineer II to join their fraud team, focusing on developing machine learning systems for real-time transaction decisions. The role involves collaborating with cross-functional teams to enhance fraud detection models and ensure their operational effectiveness

Job Summary

  • Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
  • On the ML Fraud team, you'll build and improve machine learning systems that make real-time transaction decisions, protecting consumers and merchants while balancing fraud loss, customer experience, and conversion.
  • Employees new to Affirm typically come in at the start of the pay range, with a base pay of $125,000 - $175,000 per year plus equity rewards and comprehensive benefits.

Matching Summary

Match Score: 85

Affirm is seeking a Machine Learning Engineer II to join their fraud team, focusing on developing machine learning systems for real-time transaction decisions. The role involves collaborating with cross-functional teams to enhance fraud detection models and ensure their operational effectiveness.

Salary

Base: $125,000 - $175,000 per year; Equity: Eligible for equity rewards from Affirm Holdings, Inc.; Benefits: 100% subsidized medical, dental, vision, flexible spending wallets, ESPP

Skills & Requirements

Must-have

  • 2+ years ML engineering experience
  • Python production-quality code
  • Tabular classification models
  • Gradient-boosted decision trees
  • Deep learning framework PyTorch
  • Distributed data processing Spark
  • ML lifecycle tooling Kubeflow Airflow

Nice-to-have

  • AI-powered developer tools proficiency
  • Strong verbal and written communication
  • Proactive ownership of growth
  • Experience with Ray or Dask frameworks
  • Ability to navigate large codebases

Key Requirements

  • 2+ years ML engineering experience
  • PhD in relevant field (alternative)
  • Proficiency in Python programming
  • Experience with tabular classification problems
  • Knowledge of distributed computing frameworks

Work Rights

Not specified

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