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 processes over $1T in payments volume per year, which is roughly 1% of the world’s GDP, for millions of customers from startups to enterprises. The tremendous amount of data makes Stripe one of the best places to do machine learning. While being an integral part of almost every product line at Stripe (e.g., Payments, Radar, Capital, Billing, etc.), ML is still in its early days in realizing its full potential at Stripe and is a top priority in the coming years. The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, and serving ML models. 

What you’ll do

You will work closely with ML engineers, data scientists, and platform infrastructure teams to build scalable, reliable, and flexible systems that substantially increase ML velocity across the company. 

Responsibilities

• Designing and building scalable, reliable, and flexible infrastructure that powers the end-to-end ML lifecycle at Stripe
• Creating user-friendly services and libraries that enable ML users at Stripe to seamlessly transition from experimentation to production across Stripe’s systems
• Work with a wide range of systems, processes and technologies to own and solve technical and product problems
• 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 who meet the minimum requirements to be considered for the role. The preferred qualifications are a bonus, not a requirement. 

Minimum requirements

• 3+ years of professional software development experience
• A solid engineering background and experience with service oriented architecture and large-scale distributed systems
• Familiarity with software development lifecycle, from design and implementation to testing and deployment
• Experience with operating online services with high availability and low latency
• A strong sense of curiosity and a desire to both learn and share knowledge with your peers
• Are motivated by solving hard problems and making impact by doing so
• Thrive in a highly collaborative environment involving different stakeholders and partner teams

Preferred qualifications

• Experience with building ML infrastructure and platform services
• Experience with training and shipping machine learning models to production to solve business problems