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Senior Model Risk Manager - AI/ML
Mercury is hiring for the role of Senior Model Risk Manager - AI/ML, Raleigh, NC · Remote. This is an AI Governance role in the governance, risk, and compliance field, with a posted range of $200,700 to $250,900. Review the full details below and apply directly with Mercury.
Mercury, a fintech company providing banking services for startups, is hiring a Senior Model Risk Manager - AI/ML to define what model governance looks like for AI/ML at the company. The role bridges traditional model risk management with modern AI challenges, covering the validation of predictive models, generative AI systems, and autonomous workflows.
Key responsibilities include maintaining model governance frameworks, performing independent validation, advising cross-functional teams, developing automation and tooling, and building organizational literacy around model risk in a fast-moving fintech environment. The role owns validation, monitoring, and governance of Mercury's AI/ML model portfolio.
The position is remote-eligible (US/Canada) with hybrid options at Mercury's San Francisco, New York, and Portland offices.
Qualifications
- Bachelor's in a quantitative field plus 6-10 years hands-on AI/ML development or validation experience
- Technical proficiency with Python, SQL, modern ML tooling, LLMs, RAG systems, and prompt engineering
- Experience testing ML/generative AI systems with custom evaluations or red-teaming
- Knowledge of model risk governance frameworks (SR 11-7)
- Strong communication across technical and regulatory audiences
Location and market context
This is a remote AI governance role, so it draws from a national talent pool rather than a single metro. Remote governance and compliance roles reward candidates who can show they work effectively across time zones and distributed legal, security, and product teams. Confirm any residency, travel, or occasional-onsite expectations directly with Mercury.
About AI governance roles
AI governance sits at the intersection of policy, risk, and engineering. Teams are standing up model inventories, use-case intake and review, risk classification, and control monitoring as regulation and board scrutiny of AI intensify. Roles like this one are typically evaluated against frameworks such as NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices.
How to position yourself for this AI governance role
Strong candidates emphasize experience translating policy into operational controls, working across legal, compliance, security, product, and data teams, documenting AI system risks, and supporting governance processes. In your resume and outreach, tie your experience to how Mercury would apply NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices, and lead with concrete outcomes rather than duties.
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