AI Research Scientist – Senior Associate
The goal of TTBE 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 TTBE’s clients and businesses.
TTBE 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 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 TTBE but also to the broader AI community.
Responsibilities
As a Research Scientist focused on Reinforcement Learning, you will conduct end-to-end research on topics related to single and multi-agent RL with the goal of tackling open problems such as the modeling of complex multi-agent systems and the design of safe, efficient RL algorithms for a non-stationary real world populated by strategic agents. 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, generating hypotheses, developing new algorithms and models, conducting experiments, synthesizing results, gathering data, building prototypes and communicating the significance of your research. Your output will result in publications in AI/ML conferences and journals, high-impact business applications, open source software and patents. As a member of the AI research community, you will also have the opportunity to participate in relevant top-tier academic conferences, organize workshops and engage with the community to broaden the impact of your contributions.
Skills/Experience
- ● PhD in Computer Science (especially AI/ML) or related fields
● Research publications in prominent AI/ML venues; e.g., conferences, journals
● Expertise in a related area e.g. reinforcement learning, online learning, bandits, game theory or multi-agent systems
● Practical experience with ML platforms such as Tensorflow/Keras, PyTorch, etc.
● 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
● Extensive 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
● Clear and effective verbal and written communication skills
● 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)
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