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Applied AI/ML Lead

JPMorgan Chase Bank, N.A.
INTERN Remote ยท US New York, NY, US Posted: 2026-05-11 Until: 2026-06-10
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Job Description
As part of the Commercial & Investment Bank, J.P. Morgan Payments enables organizations of all sizes to execute transactions efficiently and securely, transforming the movement of information, money and assets. We tackle complex challenges at every stage of the payment lifecycle and our industry-leading solutions facilitate seamless transactions across borders, industries and platforms. Operating in over 160 countries and handling more than 120 currencies, we are the largest processor of USD payments, with a daily transaction volume of $10 trillion. As a Vice President Applied AI/ML Scientist within our payment solutions team, you will be instrumental in utilizing artificial intelligence and machine learning technologies to augment our services and stimulate business expansion. Your role will involve researching, experimenting, developing, and implementing high-quality machine learning models, services, and platforms to streamline payment processes, bolster fraud detection, and enrich customer experience. You will also be tasked with designing and executing highly scalable and dependable data processing pipelines, conducting analysis, and deriving insights to boost and optimize business outcomes. Collaborating with cross-functional teams to pinpoint opportunities for AI/ML applications within the payment's ecosystem will also be a part of your responsibilities. Job Responsibilities: Actively collaborate with Product, Technology, and other cross-functional teams to gain a deep understanding of complex business problems and formulate data-driven solutions to address these challenges in key areas of the payments' domain. Design, develop, and deploy agentic systems using Large Language Models (LLM), machine learning and other AI solutions that meet success metrics aligned with business goals, while considering constraints such as model complexity, scalability, and latency. Partner with Risk and