Machine Learning Engineer

Join Stripe as a Machine Learning Engineer

About Stripe

Stripe is a leading financial infrastructure platform for businesses of all sizes. From the world’s largest enterprises to the most ambitious startups, millions of companies use Stripe to accept payments, grow their revenue, and create new business opportunities. Our mission is to increase the GDP of the internet. This means you have an unparalleled opportunity to impact the global economy and do the most significant work of your career.

About The Team

The Payment Intelligence ML team optimizes billions of dollars in transactions processed by Stripe annually. Our goal is to maximize successful transactions while minimizing payment costs and fraud. We leverage machine learning to provide real-time predictions as part of Stripe’s payment infrastructure and risk controls. We manage end-to-end products like Radar, Adaptive Acceptance, and Identity, operating at a lightning-fast, world-scale service level.

What You’ll Do

We are looking for Machine Learning Engineers to manage the full lifecycle of applied ML model development and deployment for consumer-facing products like Radar, Adaptive Acceptance, and Identity. You’ll work closely with software engineers, ML engineers, data scientists, and ML platform infrastructure teams to design, build, deploy, and maintain Stripe’s ML-powered payment decisioning systems.

Responsibilities

• Model Development: Design and deploy new models using tools like Spark, Presto, XGBoost, TensorFlow, and PyTorch. Improve fraud detection models to protect millions of users.
• Feature Engineering: Propose new feature ideas, design real-time data pipelines, and integrate new signals into ML pipelines.
• Model Integration: Incorporate new models into Stripe’s core payment flow.
• Cross-Functional Collaboration: Work with data science, product management, infrastructure, and risk teams to execute projects.
• Code Quality: Ensure engineering outcomes meet high standards in code quality, system design, and scalability.
• Mentorship: Mentor junior engineers to help them grow.
• Innovation: Propose and implement innovative product ideas to reduce costs and combat fraud at Stripe.

Who You Are
We welcome applications from candidates who meet the minimum requirements. The preferred qualifications are a bonus, not a requirement.

Minimum Requirements

• Over 3+ years of experience building machine learning applications in large-scale distributed systems.
• 2+ years of experience managing and optimizing ML models or ML infrastructure.
• Proven experience designing and training ML models to solve business problems.
• Strong analytical skills, including querying data, defining metrics, and evaluating model performance.

Preferred Qualifications

• Advanced degree in a quantitative field (e.g., statistics, physics, computer science).
• Proven track record of deploying effective ML systems.
• Experience in adversarial domains like Payments, Fraud, Trust, or Safety.
• Proficiency in Python, Java, and/or Ruby.
• Experience in software engineering in a production environment.

Hybrid Work at Stripe
This role is available either in-office or remote (typically, 35+ miles or 56+ km from a Stripe office).

• Office-Assigned: Spend at least 50% of your time in your local office or with users. This balance supports in-person collaboration and individual flexibility.
• Remote Location: Regularly work from home rather than a Stripe office. While you are welcome to visit the office for meetings and events, Stripe does not cover relocation costs for remote positions. Apply for roles matching your current or planned location.

Pay and Benefits

• Annual US Base Salary Range: $173,100 – $316,800. This range includes career levels at Stripe and will be narrowed based on experience, qualifications, and location during the interview process. Applicants outside the US may request their local salary range during the interview process.
• Additional Benefits: Equity, company bonuses, 401(k) plan, medical, dental, and vision benefits, and wellness stipends.

Apply Now
Join Stripe and be part of a team that’s redefining the future of payments. Apply now to make a meaningful impact on the global economy and advance your career with us.