Applied Artificial Intelligence/ Machine Learning Lead - Vice President

JobID: 210743418 Category: Predictive Science JobSchedule: Full time Posted Date: 2026-05-04T13:14:20+00:00 JobShift : As an Applied AI/ML Vice President within Global Private Bank, you'll own the full lifecycle of high-impact models serving clients across wealth management, lending, and advisory - from problem framing with business stakeholders to production deployment at scale. You'll work on some of the most data-rich, complex client problems in financial services - with the infrastructure and resources of one of the world's largest institutions behind you. We're building AI-native capabilities at the intersection of cutting-edge research and real-world impact. Job Responsibilities Define and scope AI/ML problem statements in partnership with Private Bank business leads, translating ambiguous client or operational pain points into tractable modeling problems Design, build, and deploy end-to-end ML solutions - including generative AI, NLP, and classical machine learning- across client service, risk, and operational efficiency use cases Own model quality, evaluation frameworks, monitoring, drift detection, and iteration post-deployment Drive productionization and MLOps practices in collaboration with engineering, working across distributed data infrastructure Stay current on applied research; evaluate and adapt emerging techniques - new architectures, agentic frameworks, multimodal models - for relevance to the Private Bank's problem space and translate promising work into production-ready solutions Mentor junior data scientists and help set technical standards for the team Collaborate across JPMorganChase's broader AI/ML community, model risk, compliance, and peer LOBs to align on standards, share learnings, and amplify the team's impact firm-wide Required qualifications, capabilities, and skills: Master's or PhD in Computer Science, Statistics, Applied Math, Data Science, or related quantitative field Atleast 5 years of hands-on ML experience in production environments. Deep expertise in NLP, including modern LLM fine-tuning, RAG pipelines, prompt engineering and the design and deployment of multi-step AI agents Strong Python skills; proficiency with PyTorch, TensorFlow, Scikit-learn and other libraries Experience with large-scale data processing: Spark, Hive, SQL Proven ability to communicate technical work to non-technical stakeholders Preferred qualifications, capabilities, and skills: Financial services experience