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Machine Learning Engineer, Payment Intelligence

1 week, 1 day ago
United States
Full-time
Mid Level
Machine Learning Engineer
Software Development
Apache Spark Java Machine Learning Presto Python PyTorch Ruby SQL TensorFlow XGBoost
Apply Now
Stripe

Stripe

Stripe is a global technology company that provides financial infrastructure for the internet. They offer a suite of APIs and tools for businesses to accept online and in-person payments, automate financial processes, and embed financial services in th...

Diversified Financial Services
5K-10K
Founded 2009
$8700M raised
View All Jobs 219

Description

  • Own the end-to-end lifecycle of applied machine learning model development and deployment.
  • Design and deploy new models to improve verification and fraud detection.
  • Develop new fraud detection approaches using large-scale payment datasets.
  • Propose and build real-time data pipelines to add new features and signals to models.
  • Integrate new signals into ML pipelines and create workflows that accelerate feature development.
  • Integrate new models and behaviors into Stripe’s core payment flow.
  • Collaborate cross-functionally with data science, product management, infrastructure, and risk teams.
  • Ensure code quality, system design, and scalability standards are met or exceeded.
  • Mentor engineers earlier in their careers.
  • Propose and implement product ideas that reduce costs and combat fraud.

Requirements

  • 3+ years of industry experience building machine learning applications in large-scale distributed systems.
  • 2+ years of experience on a team developing, managing, and optimizing ML models or ML infrastructure.
  • Experience designing and training machine learning models to solve critical business problems.
  • Experience performing analysis by querying data, defining metrics, and slicing data to evaluate model and business performance.
  • An advanced degree in a quantitative field such as statistics, physics, or computer science (preferred).
  • Proven track record of building and deploying machine learning systems that solved critical business problems (preferred).
  • Experience in adversarial domains such as payments, fraud, trust, or safety (preferred).
  • Experience working in Python, Java, and/or Ruby codebases (preferred).
  • Experience in software engineering in a production environment (preferred).
  • Familiarity with tools such as Spark, Presto, XGBoost, TensorFlow, and PyTorch (preferred or used in the role).

Interested in this position?

Apply directly on the company website

Apply Now

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