IBM Research takes responsibility for technology and its role in society. Working in IBM Research means you'll join a team who invent what's next in computing, always choosing the big, urgent and mind-bending work that endures and shapes generations. Our passion for discovery, and excitement for defining the future of tech, is what builds our strong culture around solving problems for clients and seeing the real world impact that you can make.
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Efficient and robust reasoning on multi-modal data have attracted many big data and AI powered computing enterprises in industry and academic research communities. Multi-modal data consists at least two or three data modalities, ranging from text (e.g., text documents, tabular, time series) to image, video, or audio. This project aims to develop systems and AI software co-design methods and optimizations to improve both efficiency and robustness of multi-modal cognitive systems in terms of inference performance and inference quality. The intern we are looking for will have the ability to work on efficient and robust AI systems based on multi-modal data, where at least two or more data modalities ranging from text, image, audio, or video are utilized. More specifically, the intern will develop AI systems and software co-design methods and optimizations to improve both efficiency and robustness of multi-modal cognitive system in terms of inference performance and quality.
- Experience with Transformers, SciPy, Scikit-learn, LangChain, LLMs, PyTorch, Github, Numpy, Tensorflow, HuggingFace
- Experience with C, Java, Python, Matlab
- Experience with AI classification, AI for images, fine tuning, AI security