Internship - Researcher / Natural Language Processing (NLP) for Multimodal Machine Learning_CVPR

About

Technology Field Natural Language Processing Machine Learning Position Summary We are an R&D organization dedicated to the research and development of large-scale generative AI technologies for content creation and production in the entertainment domain, including music, film, and games. Generative AI technologies have the potential to transform both consumer lifestyles and the workflows of professional creators, and are expected to become an essential component of the music, film, and gaming industries in the years ahead. By leveraging opportunities to collaborate directly with world-leading entertainment groups across these industries, our team engages in cutting-edge research and development to contribute to Sony Group’s businesses. For more information about our research activities and publications, please visit: https://sony.github.io/creativeai Responsibilities Fundamental research in natural language processing such as multimodal learning, multimodal LLM, music/video understanding, agent, reasoning, controllable generative modeling, deep generative models for discrete data, image/audio captioning, text-to-image/audio, vision-language pre-training, commonsense knowledge graphs, large-scale data development, etc. Submission of a research paper to top conferences (e.g. ACL, EMNLP, NeurIPS, ICLR, CVPR, etc.) is recommended. Required qualifications All of the following criteria are required. ■ Master's degree in natural language processing, artificial intelligence, machine learning, or closely related areas OR equivalent practical experience. ■ 3 years of experience with Python, C/C++, and Linux/Unix. ■ 2 years of experience in machine learning fields and NLP, using common frameworks such as PyTorch and TensorFlow. ■ Research ability, as demonstrated by a track record of conference papers, open-source software, or other scientific activities. ■ Ability to speak and write in English fluently and idiomatically. Preferred qualifications Ph.D student in natura