Responsibilities:
- Maintains the organization's AI risk taxonomy and assessment methodology, covering safety, fairness, reliability, explainability, robustness, and harmful output risks
- Develops risk evaluation rubrics for AI-specific risk dimensions (e.g., bias testing protocols, fairness metrics, explainability requirements by use case, drift tolerance thresholds, harmful output tolerances) within the established risk tolerance and acceptance thresholds
- Develops and maintains templates and standards for risk documentation (model cards, risk assessments, impact analyses, risk scorecards); project teams produce their own documentation using these templates
- Supports project teams in applying the risk assessment framework and quality gates, escalating high-risk deployments for direct review
- Executes periodic independent risk audits on a sample basis to verify that federated execution meets the standards; project QAs provide first-line coverage
- Supports red-teaming and adversarial testing coordination with the Cybersecurity team, focusing on safety, bias, and harmful output dimensions
Background & Qualifications:
- Experience in AI/ML risk management, model risk management, technology risk, or a related analytical function Working knowledge of AI-specific frameworks and legislation (NIST AI RMF, ISO 42001 & 23053, EU AI Act, and the proliferating landscape of US state-level AI legislation)
- Familiarity with risk assessment across safety, fairness, reliability, explainability, and robustness dimensions
- Hands-on experience with model evaluation, bias and fairness testing, or AI red-teaming is a plus
Skills:
- AI risk taxonomy and assessment methodology maintenance
- Developing risk evaluation rubrics: bias testing, fairness metrics, explainability, drift, and harmful output
- Risk documentation: model cards, risk assessments, impact analyses, and risk scorecards
- Model evaluation and fairness/safety testing
- Audit execution and independent risk review
- Cross-functional collaboration with Engineering and Cybersecurity
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
It is the policy of Mobility to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, Mobility will provide reasonable accommodations for qualified individuals with disabilities.
Skills Required
- Experience in AI/ML risk management, model risk management, technology risk, or a related analytical function
- Working knowledge of NIST AI RMF, ISO 42001, ISO 23053, the EU AI Act, and U.S. state-level AI legislation
- Familiarity with risk assessment across safety, fairness, reliability, explainability, and robustness dimensions
- Hands-on experience with model evaluation, bias and fairness testing, or AI red-teaming
What We Do
Mobility Global is an independent automotive intelligence company, formerly S&P Global Mobility. It provides data, analytics, connected technologies, forecasts, and expertise to organizations and consumers across the vehicle lifecycle, helping them build, buy, sell, maintain, and understand vehicles. Its offerings support decisions involving demand, risk, supply chains, sales, marketing, ownership, sustainability, and broader automotive market strategy with confidence and clarity.
