As an Intern in the 2025 AI Research, Associate Program within J.P. Morgan AI Research, you will be integral to all aspects of the research lifecycle. You will have the opportunity to work on multiple research projects, develop models and algorithms, and contribute to high-impact business applications. This role offers unique opportunities for impact within J.P. Morgan and the broader AI community

 

Job responsibilities:

Conduct end-to-end research typically within a specialized focus area.Collaborate on multiple research projects with internal and external researchers and applied engineering teams.Integrate into 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 the significance of your research.Deliver output that results in high-impact business applications, open source software, patents, and/or publications in AI/ML conferences and journals.Participate in relevant top-tier academic conferences as a member of the AI research community to broaden the impact of your contributions. 

 

Required qualifications:

Currently pursuing a PhD in Computer Science (especially AI/ML) or related field.Research publications in prominent AI/ML venues; e.g., conferences, journalsStrong expertise in one or more specialized areas of relevance to AI in Finance, e.g., LLM-based Agents, multi-agent systems, reinforcement learning / planning, 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, synthetic data and behavior understanding Practical experience with ML platforms such as Tensorflow/Keras, PyTorch, etc.Comfort with rapid prototyping and disciplined software development processesPractical software engineering experience in collaborative project settingsExtensive programming skills in PythonProficient understanding of fundamental AI and ML techniques; e.g., A*, regularizationPractical experience with statistical data analysis and experimental design

 

Preferred qualifications, capabilities and skills:

Curiosity, creativity, resourcefulness and a collaborative spiritClear and effective verbal and written communication skillsDemonstrated ability to work on multi-disciplinary teams with diverse backgroundsInterest in problems related to the financial services domain (specific past experience in the domain is not required)