Machine Learning Engineer, Capital Underwriting

Stripe

19d

About The Position

Stripe Capital provides access to fast, flexible financing to small-and-medium businesses on Stripe to accelerate their growth, and we lent over $1B in 2024. Businesses use the funds for marketing, team growth, geographic expansion, working capital, new equipment purchases, and much more. Machine learning is core to Stripe Capital’s business—we use information about businesses from their activity within and outside of Stripe and our models to automatically underwrite uniquely tailored financing offers to their needs, which banks are often unable to do. We are doing so through models with an established performance history, data infrastructure that is Stripe scale, and a strong feedback loop that includes explainability, anomaly detection and a risk portfolio management layer. We're an end-to-end team going from ideas to models to shipping in production. As a machine learning engineer for Stripe Capital, you will be responsible for designing, building, training, evaluating, deploying, and owning ML models in production with the goals of providing financing opportunities to as many users as possible while satisfying financial performance goals. You will work closely with software engineers, data scientists, product managers, and risk managers to operate Stripe’s ML powered systems, features, and products. You will also contribute to and influence ML architecture at Stripe and be a part of a larger ML community.

Requirements

• 5+ 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
• Hands-on experience in productionizing and deploying models at scale
• Hands-on experience in orchestrating complicated data pipelines and efficiently leveraging large-scale datasets
• Hands-on experience in collaborating across multiple teams, especially Data Science and Risk Management teams

Nice To Haves

• MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics)
• Proven track record of building and deploying ML systems that have effectively solved ambiguous business problems
• Experience in adversarial domains such as Lending, Trading, Fraud
• Experience with Deep Learning including the latest architectures such as transformers, test-time compute, reinforcement learning

Responsibilities

• Design state-of-the-art ML models and large scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints
• Design systems to speed up the time from idea to deployment of new models
• Experiment and iterate on ML models (using tools such as PyTorch and TensorFlow) to achieve key business goals and drive efficiency
• Develop pipelines and automated processes to train and evaluate models in offline and online environments
• Integrate ML models into production systems and ensure their scalability and reliability
• Collaborate with product and strategy partners to propose, prioritize, and implement new product features
• Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions

What This Job Offers

• Job Type: Full-time
• Career Level: Senior