Machine Learning Engineer, Capital Underwriting

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

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

Preferred Qualifications

• 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