Research Scientist - World Modeling

PhD in Machine Learning, Computer Science, Computer Vision, Robotics, or a related field, with first-author publications at top-tier venues (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, RSS, CoRL).

Research experience with state-of-the-art video generative models and world models (e.g., Cosmos-3, LTX 2.3, Self-Forcing, Lingbot-World, or comparable systems).

Deep expertise in at least one of the following areas:

Full-stack data pipelines — large-scale video data pipelines and/or simulation data collection; annotation and filtering workflows for video / world model training.

Model training & infrastructure — training large-scale diffusion transformers on large GPU clusters.

Rendering engines & simulation — Unreal Engine and Blueprint-based gym environments, game-engine integration, building interactive simulated environments.

World action models & robotics — world action models / video action models, action-conditioned video generation, world-model applications in robotics.

Strong systems and engineering expertise in deep learning frameworks such as PyTorch.

Highly proficient with modern AI coding agents and web-based coding tools (e.g., Claude Code, Codex, Cursor), and skilled at leveraging them to dramatically accelerate research workflows.

Exceptional problem-solving skills and the ability to navigate ambiguity in rapidly evolving research areas.