Research Scientist - World Modeling

Posted 22 Days Ago
Be an Early Applicant
Hiring Remotely in Abu Dhabi, ARE
Remote
Mid level
Information Technology • Automation • Manufacturing
The Role
Drive research and engineering to develop PAN world models: scalable training on large clusters, video data pipelines and annotation, evaluation benchmarks, visual tokenization, and inference optimization for real-time interaction.
Summary Generated by Built In

About the Institute of Foundation Models

The Institute of Foundation Models (IFM) at MBZUAI is a research lab dedicated to meaningful foundation model research — building models from scratch, understanding them deeply, and publishing work that shapes the field. You’ll work alongside world-class researchers and engineers on problems that directly define the models we ship.

The Role

Join the PAN world model project — our effort to build world models: foundation models that simulate, predict, and interact with the physical world. As a Research Scientist, you’ll drive the core research behind PAN — large-scale video generation, interactive and action-conditioned world models, and their applications in robotics and embodied AI — and publish at top venues while turning breakthroughs into working systems.

What You'll Do

  • Conduct original research on video world models, video diffusion models, and action-conditioned generation — from idea to publication and deployment.
  • Design pre-training and post-training recipes for large-scale diffusion transformers, including scaling-law studies for video pre-training.
  • Advance world action models / video action models and their applications in robotics and embodied agents.
  • Develop rigorous evaluation benchmarks for physical accuracy, controllability, and interactivity.
  • Collaborate with engineering and data teams on large-scale training, data curation, and simulation-based data generation.

What We're Looking For

  • 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:
    1. Full-stack data pipelines — large-scale video data pipelines and/or simulation data collection; annotation and filtering workflows for video / world model training.
    2. Model training & infrastructure — training large-scale diffusion transformers on large GPU clusters.
    3. Rendering engines & simulation — Unreal Engine and Blueprint-based gym environments, game-engine integration, building interactive simulated environments.
    4. 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.

Nice To Have

  • Experience accelerating diffusion model inference (distillation, few-step generation, real-time interactive generation).
  • Experience with visual tokenization and multimodal foundation models.
  • Experience deploying world models in robotics or embodied-AI settings.

Skills Required

  • MSc or PhD in Machine Learning, Computer Science, or equivalent industry experience
  • Experience in large-scale model training (LLMs or diffusion models) on large clusters
  • Hands-on experience with state-of-the-art video generative models (e.g., Sora, Veo2, MovieGen, CogVideoX)
  • Experience building and optimizing large-scale video data pipelines and annotation frameworks
  • Experience accelerating diffusion model inference and applying distillation techniques
  • Strong systems and engineering expertise in deep learning frameworks such as PyTorch
  • Research publications or contributions to top-tier conferences or journals (ICML, ICLR, NeurIPS, CVPR, ACL, etc.)
  • Exceptional problem-solving, troubleshooting, and ability to navigate ambiguity in research
  • Strong communication and cross-functional collaboration skills
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The Company
HQ: Essen
3,924 Employees
Year Founded: 1969

What We Do

First a passion, then an idea transformed into success – when it comes to pioneering automation and digitalisation technology, the ifm group is the ideal partner. Since its foundation in 1969, ifm has developed, produced and sold sensors, controllers, software and systems for industrial automation and for SAP-based solutions for supply chain management and shop floor integration worldwide. As one of the pioneers of Industry 4.0, ifm develops and implements consistent solutions to digitalise the entire value chain “from sensor to ERP”. Today, the second-generation family-run ifm group has more than 8,750 employees and is one of the worldwide market leaders. The group combines the internationality and innovative strength of a growing group of companies with the flexibility and close customer contact of a medium-sized company.

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