Software Engineer (ML Infra), Payment Intelligence ML

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

The Payment Intelligence ML organization optimizes each of the billions of dollars of transactions processed by Stripe annually on behalf of our customers, maximizing successful transactions while minimizing payment costs and fraud. We leverage ML to serve real-time predictions as part of Stripe’s payment infrastructure and risk controls. We own products like Radar, Adaptive Acceptance, and Identity end-to-end, operating lightning fast world-scale services and cutting-edge ML models. 

What you’ll do

You will work closely with software engineers, machine learning engineers (MLE), data scientists (DS), and platform infrastructure teams to design, build, deploy, and operate Stripe’s ML-backed payment decisioning systems.

Responsibilities

• Build machine learning systems and pipelines for training, shipping, and operating machine learning models
• Collaborate and execute projects cross-functionally with the data science, product management, infrastructure, and risk teams
• Accelerate the delivery of models to production by delivering continuous engineering improvements and investments in our MLOps infrastructure
• 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
• 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

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 2+ years of software engineering experience
• 1+ year of experience working within a team responsible for developing, managing, and optimizing ML models or ML infrastructure

Preferred qualifications

• Experience building applications that leverage real-time, distributed data processing using Flink or Spark Streaming
• Experience building batch processing pipelines using Spark
• Proven track record of building and deploying machine learning systems that have effectively solved critical business problems
• Experience with building and maintaining high availability, low latency systems, especially with respect to reliability, testing, and observability.
• Experience building sustainable operations for managing many ML models, including CI/CD, auto-training, auto-deployment, and continuous model refreshes
• Experience optimizing the end-to-end performance of distributed systems
• Experience in adversarial domains like Fraud, Trust, or Safety
• Experience working in Java and Ruby codebases