The goal of J.P. Morgan AI Research is to explore and advance cutting-edge research in AI, including ML as well as related fields like Cryptography, to develop and discover principles of impact to J.P. Morgan’s clients and businesses.

J.P. Morgan AI Research has assembled a team of experts in many fields of AI. They pursue primary research in areas related to our research pillars as well as concrete problems related to financial services. They partner with internal teams to accelerate the adoption of AI within the firm. They also work with leading academic faculty around the world on areas of mutual interest. The team is headquartered in New York and present in London, Madrid, Paris and the Bay Area. Conducting AI research in financial services offers unique and exciting opportunities for impact -- as a member of this highly visible team, you will have the opportunity to realize significant impact not only within J.P. Morgan but also to the broader AI community.

As AI Research Associate-Synthetic Data on the team, you will conduct end-to-end research typically within a specialized focus area. You will work on multiple research projects in collaboration with internal and external researchers and with applied engineering teams. You will be integral to all aspects of the research lifecycle such as formulating problems, gathering data, generating hypotheses, developing models and algorithms, conducting experiments, synthesizing results, building prototype applications and communicating the significance of your research. Your output will result in high-impact business applications, open source software, patents and/or publications in AI/ML conferences and journals. As a member of the AI research community, you will also have the opportunity to participate in relevant top-tier academic conferences to broaden the impact of your contributions.

Job Responsibilities:

As AI Research Associate-Synthetic Data in the team, you will conduct end-to-end research typically within a specialized focus area. You will work on multiple research projects in collaboration with internal and external researchers and with applied engineering teams. You will be integral to all aspects of the research lifecycle such as formulating problems, gathering data, generating hypotheses, developing models and algorithms, conducting experiments, synthesizing results, building prototype applications and communicating the significance of your research. Your output will result in high-impact business applications, open source software, patents and/or publications in security/safety conferences and journals. As a member of the Artificial Intelligence and security/safety research community, you will also have the opportunity to participate in relevant top-tier academic conferences to broaden the impact of your contributions.

Required qualifications, capabilities, and skills:

Currently pursuing a PhD in Computer Science (especially AI/ML) or related field Or a Master’s degree in Computer Science, Statistics, Engineering or related fields Research publications in prominent AI/ML venues; e.g., conferences, journals Strong expertise in one or more specialized areas of relevance to AI in Finance, e.g., synthetic data, generative AI, protecting our customers, clients, and institutional knowledge (for e.g., differential privacy, machine unlearning, membership/reconstruction attacks) and developing risk and auditing frameworks for sharing data and communications for different stakeholders, LLM alignment, watermarking. Experience in ML platforms such as Tensorflow/Keras, PyTorch, etc. Experience in rapid prototyping and disciplined software development processes Software engineering experience in collaborative project settings.

Required qualifications, capabilities, and skills:

Secondary areas of interests include LLM-based reasoning, foundational models, AI agents, planning, scheduling and optimization, AI search, multimodal document analytics, AI for coding, knowledge representation, reasoning under uncertainty, task-focused trustworthy AI, cryptography for AI, continuous learning from experience, image and language processing and understanding, large-scale complex data analytics, behavior understanding. Extensive programming skills in Python, Java or C++ Interest in problems related to the financial services domain (specific past experience in the domain is not required).