VP AI Research Lead - Innovating Secure Finance AI

J.P. Morgan; New York (NY); On-site; USD 210,000 - 320,000; Full time

Job summary

JPMorganChase AI Research is a global team delivering novel AI capabilities across the firm. As Vice President / Research Lead, you will guide research directions, collaborate with engineering and product teams, and deliver production-scale AI solutions in financial services.

Your work spans from early-stage innovation to production-scale delivery, with leadership in multi-agent systems, foundation models, reinforcement learning, and synthetic data generation.

Qualifications

• PhD in Computer Science, Engineering, or related field with AI/ML research experience.
• Publications in top AI/ML venues (e.g., NeurIPS, ICML, ICLR) or related conferences.
• Strong understanding of AI/ML techniques and experimental design.
• Excellent written and verbal communication for technical/business audiences.
• Proven software development experience with Python and tests.

Responsibilities

• Lead multiple commercially oriented AI research projects with internal teams.
• Formulate problems, run experiments, and deliver well-tested code.
• Develop reusable assets and contribute to research initiatives.
• Present findings through white papers and talks to stakeholders.
• Guide projects to production while aligning with business needs.

Skills

PhD in Computer Science

AI/ML research experience

Publications in top AI venues

Statistical data analysis

Effective communication

Python (production code)

Production deployment experience

translating business requirements

Education

PhD in Computer Science or related field

Tools

PyTorch

TensorFlow/Keras

HuggingFace Transformers

Coq/Isabelle/Lean

Z3

Job description

JPMorganChase AI Research is a global team delivering novel AI capabilities across the firm. As Vice President / Research Lead, you will guide research directions, collaborate with engineering and product teams, and deliver production-scale AI solutions in financial services.

Your work spans from early-stage innovation to production-scale delivery, with leadership in multi-agent systems, foundation models, reinforcement learning, and synthetic data generation.