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