Senior Machine Learning Engineer, Risk

Who we are

About Stripe

Stripe is a financial platform for businesses. Millions of companies—from the largest enterprises in the world to the most ambitious start-ups— use Stripe to accept payments, generate revenue, and accelerate new business opportunities. Our mission is to boost the GDP of the internet, and we have an abundance of work ahead. Thus, you have an unparalleled opportunity to make the global economy accessible to everyone while doing the most rewarding work of your career. 

About the team 

Stripe's mission is to establish the economic structure of the internet. Risk Engineering combines machine learning with product development to minimize Stripe’s financial and regulatory risk on a larger scale, while maintaining top-notch user experience. We construct ML and backend systems to catch fraudsters, comprehend users’ cash flow and financial health, and ensure Stripe’s users comply with regulatory and financial partner requirements. We shield Stripe’s brand while also protecting the company from monetary losses that could jeopardize Stripe’s business.

The Risk group consists of machine learning, backend, and full stack engineers who address this issue with innovative product ideas and powerful machine learning models. We are initiating several new projects, where you can have an extraordinary impact on the architecture, implementation, and design decisions behind these systems.

What you’ll do

As a Staff machine learning engineer, you will design and build ML models, platforms, and services that are globally configurable and scalable. You will collaborate with many departments at Stripe, with the chance to work on ML models and systems, plus provide immediate user-facing business value.

Responsibilities

• Design, train, enhance, and launch machine learning models using tools such as XGBoost, Tensorflow, PyTorch.
• Suggest and implement ideas that directly influence Stripe’s main metrics.
• Propose new feature ideas and design data pipelines to incorporate them into our models
• Improve our evaluation and monitoring of model and system performance
• Collaborate with product and engineering partners, as well as risk and policy teams, to build solutions that fulfill product needs.
• Work together with stakeholders, and lead end-to-end projects involving various technologies, and systems to successful completion.
• Provide guidance to other engineers in training and deploying new machine learning models

Who you are

We are looking for ML engineers with a strong background and passion for delivering business impacts. You are comfortable with changes, love taking initiatives, and have a bias towards action.

We are looking for someone who meets the minimum requirements for this role. If you fulfill these requirements, we encourage you to apply. Preferred qualifications are a plus but not a requisite.

Minimum requirements

• 7+ years industry experience doing software and model development on a data or machine learning team in a production environment
• Python, Scala (Spark) experience
• Experience designing and training machine learning models to solve critical business issues
• Knowledge of how to manipulate data to conduct analysis, including querying data, defining metrics, and slicing and dicing data to evaluate a hypothesis
• Highly responsible and committed when working with production systems
• Takes pride in owning projects and driving them to business impact
• Thrives in a collaborative environment

Preferred qualifications

• A postgraduate degree in a quantitative field (e.g. stats, physics, computer science) 
• Experience in the fraud or risk space
• Ruby experience
• Familiarity with NLP