IBM Research Scientists are charting the future of Artificial Intelligence, creating breakthroughs in quantum computing, disco...
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
We are seeking a Research Scientist with demonstrated publication records in the field of fairness in Natural Language Processing. As part of the IBM Research team, you will conduct world-class research on innovative technologies and solutions and publish in top-tier conferences and journals. You will also contribute to the commercialization of the resulting assets. Demonstrated communication skills and ability to work independently, as well as in a team, are highly desired traits. We are seeking a leader who is motivated by addressing AI problems and is committed to interdisciplinary engagement and collaboration with the scholarly community, with business units within IBM, and with external partners and clients. In this unique role, you will interact with the brightest minds in AI and will help bring AI research ideas into scalable, robust systems. Your can-do approach to creative problem solving will be critical to the success of your team and the company.
Required Technical and Professional Expertise
* Excellent full-stack development skills
* Proficiency in machine learning/deep learning
* Proven leadership in open-source projects
* Demonstrated publication record
* Ability to work in a team environment, as well as independently
Preferred Technical and Professional Expertise
* Deep knowledge in Neuro-Symbolic AI - including automated reasoning, natural language processing, deep learning, and scalable analysis of large knowledge graphs
* Familiarity with multilingual natural language processing
* Knowledge of trustworthy natural language processing