The Trust and Safety 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 us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.
Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.
Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date).
Responsibilities
- 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.
Minimum Qualifications:
- PhD candidate in computer science or a related technical discipline
- Related Research Experience at least one of the following areas: computer vision, multimodality, LLM
- 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 Qualifications:
- Published papers in the top AI conferences or journals is a plus, including CVPR, ICCV, ECCV, NIPS, ICML, ICLR, TPAMI, IJCV, etc
By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy