Introduction
IBM Research Scientists are charting the future of Artificial Intelligence, creating breakthroughs in quantum computing, discovering how blockchain will reshape the enterprise, and much more. Join a team that is dedicated to applying science to some of today's most complex challenges, whether it's discovering a new way for doctors to help patients, teaming with environmentalists to clean up our waterways or enabling retailers to personalize customer service.
Your Role and Responsibilities
This is for a 2025 summer internship with the following start dates: May - August or June - September for quarter system schools.
IBM Research AI's Internship Program offers an opportunity for students to work closely with IBM research scientists and engineers on cutting edge research projects with the aim of improving state of the art in artificial intelligence.
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Recent advent of large language models has shown great promise for increased productivity across a wide range of industries. However, safety and trustworthiness of these models continue to be an open problem especially for commercial applications. IBM is dedicated towards developing responsible generative AI products with a principal focus on trust enabling enterprises to feel confident in the model responses.
The next-gen Foundation Models group at IBM is looking for Research Interns to develop novel architectures in large language models with an emphasis on safety and trustworthiness. You will be working on a highly impactful and highly visible research projects on large language models of future, which are built on neuro- and cognitive science inspired architectures and training algorithms, and result into lesser hallucination, better factuality and reasoning. If you are passionate about making impactful contributions towards next generation architectures in foundation models, come join our team at IBM Research.
Required Technical and Professional Expertise
- Applicants should be PhD & MS students pursuing graduate studies.
- Experience conducting research in areas of machine learning Natural Language Processing, Deep Learning or similar.
- Programming languages and Frameworks: Python, Pytorch, Transformers, etc.
- Experience in prompting, training, or fine-tuning large Foundation Models.
Preferred Technical and Professional Expertise
- Experience with training variational autoencoders is a plus.
- Exposure in neuro-biological foundations of cognition is a plus.
- Experience publishing scientific results in technical communities such as NeurIPS, ICML, ICLR, IJCAI, ACL, AAAI, or similar.