About the Role
The J.P. Morgan AI Research team is dedicated to exploring and advancing cutting-edge research in AI, including Machine Learning and related fields like Cryptography, to generate insights beneficial to J.P. Morgan's clients and businesses. The team, comprising experts across various AI domains, conducts primary research aligned with their pillars and addresses concrete problems in financial services. They collaborate with internal teams to accelerate AI adoption within the firm and partner with leading academic faculty globally. Headquartered in New York with a presence in London and the Bay Area, this role offers unique opportunities for significant impact within J.P. Morgan and the broader AI community.
Responsibilities
- Lead end-to-end research within a specialized focus area.
- Work on multiple research projects in collaboration with internal and external researchers and applied engineering teams.
- Be integral to all aspects of the research lifecycle, including formulating problems, gathering data, generating hypotheses, developing models and algorithms, conducting experiments, synthesizing results, building prototype applications, and communicating research significance.
- Produce high-impact business applications, open-source software, patents, and/or publications in AI/ML conferences and journals.
- Participate in relevant top-tier academic conferences to broaden the impact of contributions.
Preferred Qualifications
- PhD in Computer Science (especially AI/ML) or related fields.
- Research publications in prominent AI/ML venues (e.g., conferences, journals).
- Strong expertise in one or more specialized areas, such as deep learning (DL), Reinforcement learning (RL), planning, information representation and retrieval, graphs, multiagent systems (MAS), or natural language processing (NLP).
- Practical experience with ML platforms such as Tensorflow/Keras, PyTorch.
- Comfort with rapid prototyping and disciplined software development processes.
- Practical software engineering experience in collaborative project settings.
Minimum Requirements
- Masters degree in Computer Science, Statistics, Engineering or related fields.
- Programming skills in Python, Java or C++.
- Proficient understanding of fundamental AI and ML techniques (e.g., A*, regularization).
- Practical experience with statistical data analysis and experimental design.
Professional Skills
- Curiosity, creativity, resourcefulness, and a collaborative spirit.
- Effective verbal and written communication skills with technical and business audiences.
- Demonstrated ability to work on multi-disciplinary teams with diverse backgrounds.
- Interest in problems related to the financial services domain (specific past experience in the domain is not required).