Careers - Senior Machine Learning Engineer, Model Risk Management

What you'll do

• Independently challenge model owners to reproduce results and set acceptance thresholds.
• Identify silent errors in models that cause metrics to misrepresent performance.
• Develop evaluation methods robust under real-world conditions like rare events and population shifts.
• Work hands-on in unfamiliar codebases, learning data and configurations to ship production validation tooling.
• Build agentic validation tooling for parallel agent orchestration and oversight of advanced AI systems.
• Reason about ML systems end-to-end to evaluate design decisions and challenge model owners effectively.

What we're looking for

• Senior-level experience in building or validating models in high-stakes domains like credit, fraud, or financial crime.
• Expertise in challenging model owners through reproduction, benchmarking, and stress testing to ensure model soundness.
• Proficiency in various machine learning techniques including regression, tree ensembles, and deep learning with a focus on evaluation and generalization.
• Strong software engineering skills in Python, SQL, and data engineering for production-quality code and large datasets.
• Experience with modern AI tools and frameworks, including LLMs and agentic systems, to validate advanced models.
• Knowledge of model risk management frameworks and fair-lending standards, with the ability to define validation processes for new technologies.