(General Hire) Research Scientist Graduate(TikTok Recommendation) - 2026 Start (PhD)

关于这个机会

Our team's mission is to empower genAI and content understanding in TikTok businesses. Computer vision and natural language processing are important dimensions in both content generation and understanding. We are working on various foundational models, including multi-modality pretraining, multi-modal large language model, image generation, video generation etc. As a genAI team on the business side, we try to succeed in both achieving business metric gains (recommendation metrics), and also producing state-of-the-art research outputs. This opening is part of the general hiring process for the TikTok Recommendation organization. Applications will be evaluated by multiple teams within the Recommendation organization to ensure the best alignment based on skills and interests. We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company. Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume. Responsibilities 1. Conducting development and research on cutting-edge CV, NLP, multi-modality, LLM, generative modeling 2. Following SoTA progress in relevant fields and transform the ideas into production 3. Life-cycle model development, from model training, deployment, maintenance, till its use in business scenarios.

任职要求

Minimum Qualifications: 1. Individuals who are completing or have recently completed a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field. 2. Experience in one of more areas of computer vision, natural language processing and machine learning Solid knowledge and experience with at least one major deep learning framework (e.g. PyTorch, Tensorflow, MXNet, Caffe/Caffe2). 3. Familiar with deep neural network architectures such as transformer/SSM/CNN/RNN/LSTM etc. 4. Strong analytical and problem solving skills. Ability to work collaboratively in cross-functional teams. Preferred Qualifications: 1. Authors with publications in major AI venues such as SIGGRAPH, SIGGRAPH Asia, CVPR, ICCV, ECCV, ICML, NeurIPS, ICLR

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