# Senior Model Risk Manager - AI/ML

**Company:** [Mercury](https://hotfix.jobs/companies/mercury)
**Location:** San Francisco, CA, New York, NY, Portland, OR
**Role:** Business Operations
**Salary:** $201k – $251k/yr
**Experience:** 6+ years
**Skills:** Python, SQL, scikit-learn, Xgboost, LLMs, RAG, Prompt Engineering, Ai Agent Frameworks, Model Validation, Model Risk Governance
**Posted:** 2026-05-27

> Own validation, monitoring, and governance of Mercury’s AI/ML model portfolio. Define and evolve model risk management frameworks for predictive ML, generative AI, and agentic systems in fintech.

## Job Description

## Model Governance & Monitoring Oversight
- Maintain and enhance Mercury’s model governance framework, including inventory standards, documentation templates, validation standards, and issue management.
- Assess whether first-line monitoring efforts are effective, proportionate to model risk, and sufficient to keep models fit for purpose over time.

## Model Validation
- Perform independent validation across predictive ML models, generative AI systems, and agentic workflows, covering data, assumptions, methodology, testing, and monitoring.
- Assess risks in LLM-powered applications, including RAG pipelines, tool use, autonomy boundaries, human oversight, and hallucination risk.
- Identify and document model limitations, failure modes, and emerging AI risks including drift, instability, fairness, and robustness concerns.

## MRM Advisory
- Serve as a trusted advisor to data scientists, engineers, product teams, and risk partners throughout the AI/ML lifecycle to provide practical guidance on model risk, governance expectations, and control design without slowing responsible innovation.
- Evaluate new AI use cases for regulatory implications, materiality, and governance requirements prior to deployment.
- Help shape Mercury’s responsible AI standards, including explainability, bias assessment, testing, human oversight, and documentation.

## AI Enablement for MRM
- Develop and maintain AI-enabled automation tools to improve the speed, scale, and effectiveness of model governance and validation workflows.
- Modernize the MRM function to operate effectively in a fast-moving AI environment while maintaining strong governance standards.

## Culture and Advocacy
- Champion MRM as a strategic enabler of safe and scalable AI/ML adoption, not simply a control function.
- Build model risk literacy across engineering, product, data science, compliance, and risk teams.

## Requirements
- Bachelor's degree in a quantitative field (e.g. Computer Science, Engineering, Statistics, Mathematics)
- 6-10 years of meaningful hands-on experience developing or validating AI/ML models and systems, ideally in financial services or fintech
- Strong technical foundations in Python, SQL, and modern ML tooling (e.g. scikit-learn, XGBoost)
- Familiarity with LLMs, RAG systems, prompt engineering, and AI agent frameworks
- Experience in evaluating and testing machine learning models (e.g. in fraud detection) and generative AI systems, including custom evals, red-teaming, or frameworks
- Solid understanding of model risk governance principles and regulatory expectations (e.g. SR 11-7 / OCC 2011-12, SR 26-2)
- Deep appreciation of disciplined model governance and independent effective challenge
- Comfort operating in ambiguity with the ability to synthesize fragmented technical, operational, and business context
- High agency and adaptability in a fast-moving environment
- Exceptional attention to detail across documentation, code base, testing artifacts and quantitative analysis
- Strong written and verbal communication skills

## Compensation & Benefits
- US employees (any location): $200,700 - $250,900 base salary
- Canadian employees (any location): CAD $189,700 - $237,100 base salary
- Equity and benefits included

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