Staff AI/ML Engineer

What you'll do

• Lead the design, training, and deployment of deep learning and classical ML underwriting models for credit decisions.
• Manage the full ML lifecycle from initial problem framing through production deployment, monitoring, and iteration.
• Design and improve infrastructure for feature pipelines, batch and real-time inference, and model retraining.
• Translate ambiguous business problems into technical ML solutions in partnership with Product, Engineering, and Risk teams.
• Connect model performance to business metrics and use experimentation to prove impact on member outcomes.
• Set the technical roadmap for Lending ML and establish standards for model development, validation, and governance.
• Identify opportunities where AI/ML creates measurable impact versus where simpler solutions are more appropriate.

What we're looking for

• Proven track record of leading the design and deployment of deep learning models in production for multi-quarter initiatives.
• Solid machine learning fundamentals including classical modeling, evaluation design, and metric selection.
• Hands-on experience across the end-to-end ML lifecycle including training, experimentation, optimization, deployment, and monitoring.
• Proficiency in Python and SQL with deep learning frameworks like PyTorch and distributed compute like Spark or PySpark.
• Working knowledge of modern ML infrastructure including AWS, SageMaker, Airflow, Kafka, Redis, and Snowflake.
• Ability to operate independently in ambiguous environments and influence technical direction across teams.
• Experience in credit or underwriting models, model governance, explainability, and fairness requirements (preferred).
• Experience in cash flow/alternative-data underwriting or deploying transformer models in production (preferred).