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Artificial Intelligence Research Scientist, Reinforcement Learning And Multi-Agent Learning/Simulation- Vice President
Company | JPMorgan Chase & Co. |
Address | New York, NY, United States |
Employment type | FULL_TIME |
Salary | |
Category | Financial Services |
Expires | 2023-08-29 |
Posted at | 9 months ago |
The goal of JPMorgan Artificial Intelligence Research is to explore and advance cutting edge research in Artificial Intelligence, including Machine Learning as well as related fields like Cryptography, to develop and discover principles of impact to JPMorgan's clients and businesses.
- Your output will result in high-impact business applications, open source software, patents and/or publications in security/safety conferences and journals.
- As a Research Scientist 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.
- 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.
- 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.
- Solid understanding of the application of fundamental Artificial Intelligence and Machine Learning techniques to security/safety; e.g, Natural Language Processing based approaches to understanding security content; detecting anomalous activity
- PHD with 4 + years of relevant work experience or Master' s degree with 6+ years of relevant work experience in Computer Science, Statistics, Engineering or related fields . Research publications in prominent AI/ML venues; e.g., conferences, journals
- Practical experience with ML platforms such as Tensorflow/Keras, PyTorch , etc.
- Experience with building, tuning and evaluating NLP models including text classification, topic modeling, and data extraction.
- Expertise in a related area e.g. reinforcement learning, online learning, bandits, game theory, mechanism design, agent-based modeling, discrete-event systems.
- Demonstrated ability to work on multi-disciplinary teams with diverse backgrounds
- I nterest in problems related to the financial services domain (specific past experience in the domain is not required)
- Curiosity, creativity, resourcefulness and a collaborative spirit
- Clear and effective verbal and written communication skills
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