Software Engineer, Machine Learning Infrastructure

  • Stripe
  • Seattle, WA, USA
  • Sep 16, 2022
Full-time Data Science Java Machine Learning Python Software Development Software Engineering

Job Description

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 o 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

  • Building powerful, flexible, and user-friendly infrastructure that powers all of ML at Stripe
  • Designing and building fast, reliable services for ML model training and serving, and scaling that infrastructure across multiple regions
  • Creating services and libraries that enable ML engineers at Stripe to seamlessly transition from experimentation to production across Stripe’s systems
  • Pairing with product teams and ML engineers to develop easy-to-use infrastructure for production ML models

Who you are

We’re looking for people with a strong background or interest in building successful products or systems; you’re passionate about solving business problems and making direct impact on customers, you are comfortable in dealing with lots of moving pieces; and you’re comfortable learning new technologies and systems.

Minimum requirements

  • Over 5 years of experience building software applications in large scale distributed systems 
  • A strong sense of curiosity and a desire to both learn and share knowledge with your peers. We like to work in a collaborative environment and hope you do too.
  • A solid engineering background and experience with infrastructure and/or distributed systems. You’ll work mostly in Python and Java but we care more about your general engineering skills than your knowledge of a specific language.
  • Familiarity with the full life cycle of software development, from design and implementation to testing and deployment.
  • Experience with building and maintaining high availability, low latency systems, especially with respect to reliability, testing, and observability.
  • A sense of pragmatism: you know when to aim for the ideal solution and when to adjust course.

Preferred qualifications

  • Over 2 years of experience supporting Machine Learning Infrastructure.
  • Experience optimizing the end-to-end performance of distributed systems.
  • Experience training and shipping machine learning models to production to solve critical business problems.

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.