Pursue a critical career at the intersection of advanced technology and financial integrity with AVP ML and GenAI Model Validation jobs. This senior professional role sits within the model risk management framework of heavily regulated industries, primarily financial services, and is dedicated to ensuring the robustness, fairness, and reliability of sophisticated Artificial Intelligence and Machine Learning models. An Assistant Vice President (AVP) in this field leads a technical team responsible for the independent vetting and approval of models that drive key business decisions, customer interactions, and strategic innovations. Professionals in these jobs act as the essential gatekeepers of model risk. Their core mission is to provide rigorous, objective challenge to models developed by quantitative teams. Common responsibilities include conducting deep-dive validation assessments on a wide range of models, from traditional credit risk scoring algorithms to cutting-edge Generative AI and Large Language Model (LLM) applications. This involves evaluating a model's conceptual soundness, data quality, performance stability, and implementation integrity. They meticulously test models against their intended use, identifying inherent limitations, potential biases, and operational risks. A key output is the production of comprehensive validation reports that document findings and prescribe actionable recommendations for model enhancement or risk mitigation, ensuring clear communication to both technical teams and senior management. The typical skill set for this profession is highly interdisciplinary. Candidates generally possess an advanced degree (Master's or PhD) in a quantitative field such as Computer Science, Statistics, Mathematics, or Financial Engineering. Hands-on technical expertise is non-negotiable, including proficiency in Python/R, ML frameworks (TensorFlow, PyTorch), and big data environments (AWS, Hadoop). Specifically for GenAI validation, experience with transformer architectures, Retrieval-Augmented Generation (RAG) systems, prompt engineering techniques, and evaluation frameworks is increasingly essential. Beyond technical acumen, a deep understanding of model risk management principles and relevant regulatory guidance (like SR 11-7 or the EU AI Act) is critical. Success in these jobs hinges on strong analytical prowess, impeccable attention to detail, and exceptional communication skills to articulate complex model nuances to diverse stakeholders. For those seeking to shape the responsible deployment of AI in the enterprise, AVP ML and GenAI Model Validation jobs offer a challenging and impactful career path.
