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.