Drimva

TikTok

Tech Lead Research Scientist/Software Engineer, TikTok-Neural Graphics and World Models

San Jose, California · Full-time · Posted Oct 28, 2026

Experience
5 years of relevant research or industry experience; doctoral research may count toward this experience.
Education
PhD/MS, or equivalent research experience, in machine learning, computer graphics, robotics, applied mathematics, or a related technical field.

About the job

Leads research and engineering for AI models and neural representations that generate and power interactive graphics and persistent digital worlds.

What you'll do

  • Lead research in neural graphics, world models, 3D modeling, animation, simulation, or rendering; develop and evaluate models and representations.
  • Define data and evaluation strategies, build research prototypes, and collaborate with engineering teams to integrate successful models into real-time engine workflows.
  • Analyze results and risks, communicate technical direction, produce reproducible research artifacts, and mentor team members.

What they ask for

  • PhD/MS, or equivalent research experience, in machine learning, computer graphics, robotics, applied mathematics, or a related technical field.
  • 5 years of relevant research or industry experience; doctoral research may count toward this experience.
  • Up-to-date machine learning expertise and hands-on experience training or adapting generative models; engineering fluency with PyTorch or JAX.
  • Deep expertise in at least one AI-for-graphics area, plus demonstrated ability to design controlled experiments and translate research prototypes into engine pipelines.

Nice to have

  • Publications at leading research venues such as SIGGRAPH, CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, RSS, or CoRL.
  • Experience with AI-for-graphics architectures, data and evaluation methods; multimodal or controllable world generation; interactive learning or control; or real-time engine workflows.

Tools

PyTorch, JAX, variational autoencoders, latent tokenizers, diffusion or flow-matching models, diffusion transformers, autoregressive models, multimodal transformers

AI focus

Develops, trains, and evaluates AI models and neural representations for interactive graphics, world generation, animation, simulation, and rendering.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)