Machine Learning Engineer, Identity Product

Help increase the GDP of the internet as part of our Risk team. 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 own Identity 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 Design and deploy new models using tools (such as Spark, Presto, XGBoost, Tensorflow, PyTorch) and iteratively improve verification and fraud models to protect millions of users from fraud Integrate new signals into ML pipelines, derive new ML features, and build workflows to make this process fast Integrate new models and behaviors into Stripe's core payment flow Propose and implement innovative product ideas to reduce costs and combat fraud at Stripe Collaborate and execute projects cross-functionally with the data science, product management, infrastructure, and risk teams 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 6+ years of industry experience building and shipping ML systems in production Proficient with ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, as well as Spark Knowledge of various ML algorithms and model architectures Hands-on experience in designing, training, and evaluating machine learning models Experience performing analysis, including querying data, defining metrics, or slicing and dicing data to model performance and business metrics Preferred qualifications MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics) Experience with DNNs including the latest architectures such as transformers and LLMs Experience working in Java or Ruby codebases Proven track record of building and deploying ML systems that have effectively solved ambiguous business problems Experience in adversarial domains such as Payments, Fraud, Trust, or Safety

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.