Machine Learning Engineer, Identity Product

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.

Machine Learning at Stripe

Machine learning is an integral part of almost every service at Stripe. Key products and use-cases powered by ML at Stripe include merchant and transaction risk, payments optimization and personalization, identity verification, and merchant data analytics and insights. We are also using the latest generative AI technologies to re-imagine product experiences, and are developing AI Assistants both for our customers and to make Stripes more productive across Support, Marketing, Sales, and Engineering roles within the company.

Stripe handles over $1T in payments volume per year, which is roughly 1% of the world’s GDP. We process petabytes of financial data using our ML platform to build features, train models, and deploy them to production. We use a combination of highly scalable and explainable models such as linear / logistic regression and random forests, along with the latest deep neural networks from transformers to LLMs. Some of our latest innovations have been around figuring out how best to bring transformers and LLMs to improve existing models and enable entirely new product ideas that are only made possible by GenAI. Stripe’s ML models serve millions of users daily and reduce financial risk, increase payment success rate, and grow the GDP of the internet. We work on challenging problems with large business impact, and seek to foster creativity and innovation.

About the team

Before Stripe, every growing internet platform had a payments team. Today, every growing internet platform has an Identity team to verify trustworthiness of a user. Identity verification is a core piece of economic infrastructure for online businesses that enables businesses to digitally verify the user’s Identity (through ID document, Passport, DL) for fraud, regulatory and trust & safety purposes. At Stripe, we're building the future of identity verification and trust in the digital economy.

Why Stripe Identity?

• Be part of a team that's building a product with the potential to transform how trust is established in the digital world
• Work on challenging technical problems at a global scale
• Contribute to a product that will serve diverse industries, from fintech to e-commerce and beyond
• Opportunity to shape the future of digital identity and fraud prevention

We leverage ML to serve real-time predictions as part of Stripe’s payment infrastructure and risk controls. We ownIdentity end-to-end, operating lightning fast world-scale services and cutting-edge ML models. We’re looking for people with a strong background or interest in building successful products while keeping user first perspective, who have the ability to deal with ambiguity, exquisite attention to detail and who are comfortable learning new technologies and systems.

What you’ll do

We are looking for Machine Learning Engineers to own the end-to-end lifecycle of applied ML model development and deployment in service of consumer facing product Identity . You will work closely with software engineers, machine learning engineers (MLE), data scientists (DS), and ML platform infrastructure teams to design, build, deploy, and operate Stripe’s ML-powered decisioning systems, including improving existing ML models and developing new ML solutions.

Responsibilities

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.

Preferred qualifications

This role is available either in an office or a remote location (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 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 live or plan to live.

The annual US base salary range for this role is $212,000 - $318,000. 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.

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.

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