The Machine Learning Engineer for Stripe Capital will design, build, and deploy machine learning models to provide tailored financing opportunities for small and medium businesses. This role is crucial for enhancing Stripe's underwriting processes and involves collaboration with software engineers, data scientists, and product managers. The team focuses on leveraging machine learning to automate and optimize financing offers, ensuring scalability and reliability in production systems. The position offers an opportunity to influence ML architecture and contribute to a larger ML community within Stripe.

• 5+ years of industry experience building and shipping ML systems in production
• Proficient with ML libraries and frameworks such as PyTorch, TensorFlow, and XGBoost
• 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

• Design state-of-the-art ML models and large scale ML systems for underwriting and portfolio management for Stripe Capital.
• 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.
• 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.