Senior Quant, Artificial IntelligenceMachine Learning

Were looking for a sharp individual contributor whos adept at advanced AI/ML algorithms and their applications in financial institutions to join our AI/ML Validation Center of Excellence in Model Risk Management. The team plays a critical role in providing oversight to U.S. Banks Artificial Intelligence Models across various business areas such as Marketing Fraud Credit Risk and Bank Operations.

As a Senior Quant you will develop benchmark AI/ML models provide validation expertise and consulting services related to AI/ML model development and model review including best practices on algorithm development and selection performance evaluation implementation monitoring model risk mitigation and addition you will be responsible for conducting R&D for various AI/ML methodologies and their potential applications and use cases.

Deliverables include reviewing model development documentation independently testing of advanced AI/ML and Generative AI & Agentic AI models developing technical guidance documents training curriculum and white paper and communicating model requirements and validation outcome to stakeholders within the Bank.

- Strong statistical modeling or computer science background and hands on model development or validation skills

- Strong programming skillsusing Python packages such as Numpy Pandas and scikit-learn.

- Considerable knowledge of various machine learning algorithms and their applications including Random Forest GBM XGBoost deep learning NLP computer vision and LLM.

- Hands-on experience designing developing and deploying advanced deep learning architectures including MLPs RNNs CNNs and other state-of-the-art neural network frameworks for a wide range of AI and machine learning applications.

- Deep expertise in advanced Agentic AI architectures and orchestration patterns including function calling MCP SKILLs A2A context engineering harness engineering loop engineering and other emerging frameworks for building scalable multi-agent AI systems.

- Strong expertise in building deploying and evaluating GenAI and Agentic AI solutions including RAG multi-agent systems tool-augmented workflows and advanced evaluation techniques such as adversarial testing semantic similarity analysis retrieval assessment and LLM-as-a-Judge methodologies.

- Hands-on experience with modern AI development deployment and evaluation ecosystems including PyTorch TensorFlow/Keras Hugging Face Transformers LangChain LangGraph OpenAI Agent SDK AI-assisted development platforms such as Claude Code and GitHub Copilot and LLM evaluation frameworks including DeepEval LlamaIndex Ragas and other comparable tools.

- Familiarity with cloud-based AI platforms and services including AWS Bedrock Azure AI Microsoft Copilot Google Vertex AI vector databases and model serving/inference platforms.

- Research experience and publications on AI or Gen AI are preferred

- Experience in financial industry is preferred but not required

- Advanced understanding of Model Risk Management and OCC SR 26-2 is a plus

- Demonstrated independence teamwork and leadership skills
- Strong project management skills
- Excellent written and verbal communication skills

LOCATION EXPECTATIONS: This role requires working from a U.S. Bank Location three (3) or more days per week.