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

The Machine Learning Infrastructure organization provides infrastructure
and support to run machine learning workflows and ship to production,
tooling and operational capacity to accelerate the use of these
workflows, and opinionated technical guidance to guide our users onto
successful paths.

What you’ll do

You will  work closely with machine learning engineers, data scientists,
and platform infrastructure teams to build the powerful, flexible, and
user-friendly systems that substantially increase ML-Ops velocity
across the company.

Responsibilities

• Create long term technical vision for the org, and identify paths to
  deliver value in shorter term phases
  
• Lead the 0-1 delivery of powerful, flexible, and user-friendly
  infrastructure that powers all of ML at Stripe
  
• Designing and building fast, reliable services for ML feature
  engineering, model training and model serving, and scaling that
  infrastructure across multiple regions
  
• As a leader within Engineering, assist with team growth and
  development while maintaining a high bar for excellence and and
  technical curiosity
  
• Create services and libraries that enable ML engineers at Stripe to
  seamlessly transition from experimentation to production across
  Stripe’s systems
  
• Own and build cross-functional partnerships with stakeholders
  including dependency engineering teams, product, design,
  infrastructure, and operations
  

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

• Minimum of 15+ years of engineering experience OR equivalent combined
  work experience reflecting domain expertise as relevant to this
  position 
  
• Demonstrated experience of leading company-wide initiatives spanning
  multiple teams and organizations OR leveraging deep domain expertise
  to influence tech roadmap planning and execution
  
• Demonstrated ability to effectively collaborate across multiple teams
  and stakeholders to drive business outcomes 
  
• Demonstrated ability to balance execution and velocity with security,
  reliability, and efficiency
  
• Experience, mentoring, and investing in the development engineers and
  peers 
  

Preferred qualifications

• Experience optimizing the end-to-end performance of distributed
  systems.
  
• Experience designing and implementing data processing systems using
  the lambda architecture.
  
• Experience debugging and optimizing large scale data pipelines using
  Apache Spark.
  
• Experience training and shipping machine learning models to production
  to solve critical business problems.