Staff Machine Learning Infrastructure Engineer (Technical Leader)

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. 

Office locations

South San Francisco HQ, or Seattle

Remote locations

Remote in United States

Team

Data & Data Science

Job type

Full time

For candidates or potential candidates based in Colorado, please reach out to colorado-wages@stripe.com to request compensation and benefits information regarding particular roles. Please include the city in Colorado where you reside and the titles of the applicable roles and/or links to the roles along with your request.

We look forward to hearing from you

At Stripe, we're looking for people with passion, grit, and integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills and passion will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns. At Stripe, we welcome diverse perspectives and people who think rigorously and aren't afraid to challenge assumptions. Join us.