Track and explore key technologies related to large models such as CV, NLP, multimodality, etc., participate in the development of pre-training large models, and work on investment and research for AI projects.
Requirements:
Master's degree or above in artificial intelligence, computer science, communication, automation, or related fields.
Have certain scientific research capabilities, the ability to quickly learn new technologies, and the ability to read and understand academic papers in relevant fields.
Proficient in at least one development language such as Python, C++, and familiar with at least one framework such as Pytorch/TensorFlow/PaddlePaddle/MindSpore. Candidates with experience in training large models for CV and NLP, such as CAE, MAE, Transformer, Diffusion, are preferred. Those with experience in industry typical large model training and tuning are preferred.
Candidates with experience in developing large-scale distributed algorithms are preferred.
Priority will be given to those who have published papers in related conferences such as computer vision (CVPR, ICCV, ECCV) and machine learning (NIPS, ICML, AAAI).
Ability to deploy high-quality models in production environments.