Machine Learning Engineer, Risk

Who we are

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

Stripe’s mission is to build the economic infrastructure for the internet. Risk Engineering brings together machine learning with product development to lower Stripe’s financial and regulatory risk at scale, while retaining a best in class user experience. We build ML and backend systems to catch fraudsters, understand users’ cash flow and financial health, and ensure Stripe’s users are compliant with regulatory and financial partner requirements. We protect Stripe’s brand while also protecting the company from financial losses that can put Stripe’s business at risk.

The Risk group consists of machine learning, backend, and full stack engineers who tackle this problem through creative new product ideas and impactful machine learning models. We are undertaking several new efforts, where you can have an outsized impact on the architecture, implementation, and design choices behind these systems.

What you’ll do

Responsibilities

• Designing, training, improving & launching models 
• Proposing and implementing ideas that directly reduce Stripe’s financial losses
• Building systems that evaluate businesses for risk and take appropriate actions
• Working with our partner teams to launch new policies that directly impact Stripe’s bottom line
• Helping engineers across the company to develop technologies for scaling our infrastructure
• Debugging production issues across services and multiple levels of the stack

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

• Have at least 2 years of industry experience in training ML models
• Enjoy and have experience shipping ML models in a large-scale production environment
• Hold yourself and others to a high bar when working with production systems
• Take pride in taking ownership and driving projects to business impact
• Thrive in a collaborative environment

Preferred qualifications

• Have experience in Python, Scala (Spark), or Ruby