Research Engineer/Scientist (all levels), World Models

  • Tiktok
  • San Jose, California
  • Full Time

About the TeamThe Vision-Applied Research team focuses on applied research in Generative AI and CV/Multimodal Understanding, and delivering intelligent solutions to Tiktok, enabling users to make and share creative content in a much easier way. The team has research groups dedicated to generative models for content creation, image generation, video synthesis, intelligent image/video editing, and world models.

The team is looking for Research Engineer / Scientists who can take initiatives in building next-generation World Models. The candidate will work on developing methods and infrastructure to train large-scale generative models from massive simulated and real-world multimodal datasets. This role places a particular emphasis on ensuring long-horizon temporal consistency, realistic physics, complex dynamics from the model and enabling users and agents to interact with the model in real-time.

Responsibilities

  • Develop large-scale, diverse, and interactive multi-modal data generation pipeline.
  • Develop training pipeline for long-context interactive video generation models.
  • Advance video generation models to capture long-horizon temporal consistency, realistic physical dynamics, object interactions, and causal relationships from large-scale multi-modal data.Minimum Qualifications:
  • M.S or Ph.D. in Computer Vision, Computer Graphics, Machine Learning, or equivalent experience.
  • Extensive research experiences in broad GenAI, multimodal foundation models, or Embodied AI areas.
  • Demonstrated ability to communicate complex technical concepts and collaborate effectively within cross-functional research teams

Preferred Qualifications:

  • Proven experiences in at least one of the following areas: video generation and synthesis; efficient and real-time diffusion models; 3D/physics-based simulation; or reinforcement learning for agentic environment interaction.
  • Proven track record of first-author publications in prestigious venues including CVPR, ICLR, NeurIPS, SIGGRAPH, and ICML
Job ID: 516278967
Originally Posted on: 4/6/2026

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