In our team, you will have the opportunity to participate in the development of the cutting-edge content understanding model to help improve the recognition ability of violated content in TikTok, and will also be responsible for optimizing our distributed model training framework continuously.
Develop computer vision model or multimodality model to recognize violation content in TikTok
Explore cutting-edge multimodal or computer vision large models (CLIP, COCA, ALBEF, BLIP, Flamingo, ViT-G, ViT-22B, EVA-enormous, etc)
Explore the application of LLM in our business scenarios, like pre-training, zero-shot/ few-shot learning, hard case mining, etc
Continuously optimize the training framework to better adapt to the training of large models
Requirements
Successful candidates must be able to commit to an onboarding date by the end of the year.
Please state your availability and graduation date clearly in your resume.
Individuals who are completing or have recently completed a PhD degree in computer science or a related discipline.
Be proficient with at least one deep learning framework (e.g. PyTorch, TensorFlow)
Have excellent analytical and problem-solving skills, logical thinking skills, communication and collaboration skills
Preferred
Related Research Experience at least one of the following areas: computer vision, multimodality, LLM
Published papers in the major AI conferences or journals is a plus, including CVPR, ICCV, ECCV, NIPS, ICML, ICLR, TPAMI, IJCV, etc
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