About the job
The algorithm team is responsible for developing state-of-the-art computer vision, NLP and multimodality models and algorithms to protect our platform and users from the content and behaviors that violate community guidelines and related regulations. With the continuous efforts from our team, TikTok is able to provide the best user experience and bring joy to everyone in the world. We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok. 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. 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. Develop computer vision model or multimodality model to recognize violation content in TikTok
2. Explore cutting-edge multimodal or computer vision large models (CLIP, COCA, ALBEF, BLIP, Flamingo, ViT-G, ViT-22B, EVA-enormous, etc)
3. Explore the application of LLM in our business scenarios, like pre-training, zero-shot/ few-shot learning, hard case mining, etc
4. Continuously optimize the training framework to better adapt to the training of large models
Qualifications
Minimum
1. Individuals who are completing or have recently completed a PhD degree
2. Related Research Experience at least one of the following areas: computer vision, multimodality, LLM
3. Be proficient with at least one deep learning framework (e.g. PyTorch, TensorFlow)
4. Have excellent analytical and problem-solving skills, logical thinking skills, communication and collaboration skills
Preferred
1. Published papers in the major AI conferences or journals is a plus, including CVPR, ICCV, ECCV, NIPS, ICML, ICLR, TPAMI, IJCV, etc