What are the responsibilities and job description for the Research Scientist - Time Series Foundation Models position at IBM?
Introduction
Are you interested in time series foundation models, the new model architectures and driving impact from fundamental research all the way to clients and products? Are you passionate about developing systems that make a real-world impact? Would you enjoy publishing your work in the most prestigious AI conferences in the world, and making your code open source? If you answered yes to these questions, then you should apply to our research scientist position at IBM. We are seeking highly motivated students with background in multimodal LLMs to join our team.
Your role and responsibilities
You will be responsible to conduct cutting-edge research and development on time series foundation models for a wide variety of enterprise use cases. In this role, you are expected to develop high quality software to support novel AI model architectures, new techniques for training and tuning, synthetic data generation and push the frontiers on multi-task time series foundation models.
Required technical and professional expertise
Solid knowledge of latest time series foundation model architectures including TS transformer models, statistical models, TTM, etc.
Hands-on experience with time series foundation models and their training and tuning
Strong programming skills and familiarity with the FM frameworks and libraries such as pytorch, distributed training, etc.
Great problem solving skills, with a strong desire for high quality and high impact research and engineering excellence
Master’s or PhD degree in Computer Science, Electrical Engineering, Mathematics, Operations Research
Preferred technical and professional experience
Strong publication record with either publications in top peer-reviewed scientific conferences and journals or strong leadership track-record in open source communities, with a particular focus on foundation models in time series domain.
