Research Scientist, Multimodal and Generative AI-TikTok Recommendation

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.

Responsibilities
1. Conducting development and research on cutting-edge CV, NLP, multi-modality, LLM, generative modeling
2. Following SoTA progress in relevant fields and transforming ideas into production
3. Life-cycle model development, from model training, deployment, and maintenance, to its use in business scenarios.

Minimum Qualifications:
1. PhD 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
3. Solid knowledge and experience with at least one major deep learning framework (e.g. PyTorch, Tensorflow, MXNet, Caffe/Caffe2).
4. Familiar with deep neural network architectures such as transformer/SSM/CNN/RNN/LSTM etc.
5. Strong analytical and problem solving skills. Ability to work collaboratively in cross-functional teams.

Preferred Qualifications:
1. Degree in computer science, electrical engineering or related fields
2. Authors with publications in top-tier venues such as SIGGRAPH, SIGGRAPH Asia, CVPR, ICCV, ECCV, ICML, NeurIPS, ICLR