Stripe is a financial infrastructure platform for businesses, aiming to increase the GDP of the internet. They are seeking a Machine Learning Engineer to manage the end-to-end lifecycle of applied ML model development and deployment, particularly for consumer-facing products in payment intelligence.
Responsibilities:
- Design and deploy new models using tools (such as Spark, Presto, XGBoost, Tensorflow, PyTorch) and iteratively improve verification and fraud models to protect millions of users from fraud
- Envision and develop new models for fraud detection i.e work with large payment datasets to find creative new methods of detecting and deterring fraudulent behavior
- Propose new feature ideas and design real-time data pipelines to incorporate them into our models
- Integrate new signals into ML pipelines, derive new ML features, and build workflows to make this process fast
- Integrate new models and behaviors into Stripe’s core payment flow
- Collaborate and execute projects cross-functionally with the data science, product management, infrastructure, and risk teams
- Ensure engineering outcomes meet or exceed established standards of excellence in code quality, system design, and scalability
- Mentor engineers earlier in their technical careers to help them grow
- Propose and implement innovative product ideas to reduce costs and combat fraud at Stripe