Machine Learning Engineer, Credit Intelligence

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

Credit Intelligence brings together machine learning with product development to lower Stripe’s credit risk at scale, while retaining a best in class user experience.  Getting this tradeoff right is critical to Stripe’s long term success and profitability. We protect Stripe’s brand while also protecting the company from credit losses that can put our financial position at risk.

The Credit Intelligence team consists of machine learning, backend, and full stack engineers who want to tackle this problem through creative new product ideas and impactful machine learning models. We are undertaking several new efforts, where you can have an outsized impact on the architecture, implementation, and design choices behind these systems. 

What you’ll do

• Design and deploy new models to iteratively improve Stripe’s business-critical models and systems that understand a user’s credit risk
• Build the next generation of model training and scoring infrastructure, in close collaboration with our infrastructure teams
• Imagine new feature ideas and design data pipelines to incorporate them into our models
• Improve the way we evaluate and monitor our model and system performance

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

• An advanced degree in a quantitative field (e.g. computer science, stats, physics, engineering)
• 3+ years experience in software engineering in a production environment
• Experience designing and training machine learning models to solve critical business problems
• Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis

Preferred qualifications

• The ability to thrive in a collaborative environment involving different stakeholders and subject matter experts
• Pride in working on projects to successful completion involving a wide variety of technologies and systems

Hybrid work at Stripe

This role is available either in an office or a remote location (typically, 35+ miles or 56+ km from a Stripe office).

Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.

A remote location, in most cases, is defined as being 35 miles (56 kilometers) or more from one of our offices. While you would be welcome to come into the office for team/business meetings, on-sites, meet-ups, and events, our expectation is you would regularly work from home rather than a Stripe office. Stripe does not cover the cost of relocating to a remote location. We encourage you to apply for roles that match the location where you currently or plan to live.

Pay and benefits

The annual US base salary range for this role is $180,000 - $270,000. 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.

We look forward to hearing from you

At Stripe, we're looking for people with passion, grit, and integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills and passion will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns. At Stripe, we welcome diverse perspectives and people who think rigorously and aren't afraid to challenge assumptions. Join us.