We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. 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.
About the Team The Intelligent Creation – Global GenAI team focuses on applied research in Generative AI, delivering intelligent creation solutions for the TikTok platform. Our mission is to empower users to create and share high-quality content with ease. The team works on cutting-edge areas including multimodal foundation models, image and video generation and editing, efficient model design, and world models.
Responsibilities
- Conduct research and development in generative AI and multimodal models (e.g., image, video).
- Develop large-scale foundation models (LLMs/VLMs), through post-training techniques.
- Design and build models for creative applications on the TikTok platform, driving end-to-end impact from research to production through cross-functional collaboration.
- Explore new AI-driven product opportunities and contribute to next-generation creative experiences.
Minimum Qualifications:
- Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline
- Proficiency in training generative AI or large models using frameworks such as PyTorch or JAX.
- Strong programming skills and solid fundamentals in machine learning.
- Strong problem-solving ability and motivation to tackle real-world challenges.
- Good communication and collaboration skills in fast-paced environments.
Preferred Qualifications:
- Ph.D. in Generative AI, Machine Learning Systems, or a related field, or equivalent experience.
- Strong research background in one or more areas: generative AI, LLMs/VLMs, or ML systems.
- Hands-on experience in at least one of the following areas: Image/video generation and editing; VLM/LLM fine-tuning; Efficient model design and optimization; Reinforcement learning methods (e.g., RLHF, DPO, GRPO)
- Track record of research publications in conferences such as CVPR, ECCV, ICCV, NeurIPS, ICLR, SIGGRAPH, or SIGGRAPH Asia.