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.
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.
The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training and deploying models, and MLOps for end-to-end automation. We work closely with ML engineers, data scientists, and platform infrastructure teams to build the powerful, flexible, and user-friendly systems that substantially increase ML velocity across the company
You will have the opportunity to shape the future of doing ML efficiently and scalably at Stripe. You will help define the long-term strategy and lead the team in building the next generation of ML foundations that power most if not all of Stripe’s products.
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.
The annual US base salary range for this role is $224,300 - $336,500. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.
Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.
Office locations
Seattle
Team
Machine Learning
Job type
Full time