Lead Applied AI & Machine Learning Engineer

JPMorganChase is a global financial institution providing banking, financial services, and technology solutions to consumers, businesses, and institutional clients. The Applied AI and Machine Learning Lead will develop generative AI and machine learning solutions from concept through production, lead enterprise semantic modeling and ontology strategies, establish governed semantic integrations, and mentor technical talent.

Responsibilities:

• Build generative AI, agentic AI, and large language model solutions in Python from proof of concept through production deployment with measurable outcomes
• Design context engineering approaches to improve model accuracy, latency, reliability, and end-to-end user experience
• Lead enterprise semantic modeling strategy, including ontology standards, governance practices, and lifecycle management
• Partner with domain experts to create scalable ontologies that represent business entities, relationships, rules, and constraints
• Define semantic integration patterns across data pipelines, application programming interfaces (APIs), data contracts, and experience layers to resolve semantic conflicts
• Establish and govern a unified semantic layer that enables trusted analytics across business intelligence, machine learning, and transactional systems
• Enable intelligent workflows and AI agents using ontology-driven context, semantic reasoning, and orchestration approaches
• Build and maintain pipelines and frameworks for model training, evaluation, optimization, monitoring, and machine learning operations
• Implement responsible AI practices, model risk controls, and governance aligned to regulated environments
• Mentor engineers and data scientists, raising the bar on engineering rigor, reuse, and continuous improvement across the team