• 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

Desirable

• 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
• 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
• 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