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World Model Lead

Institute of Foundation Models

Abu Dhabi

On-site

AED 200,000 - 300,000

Full time

9 days ago

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Job summary

A research institution in Abu Dhabi seeks an experienced leader for world modeling efforts. The role involves defining model architecture, managing multidisciplinary teams, and driving projects. A Ph.D. or M.S. with extensive AI and simulation experience is required. The successful candidate will play a critical role in AI development and shape next-gen solutions. This position offers a dynamic environment focused on innovation and collaboration.

Qualifications

  • Ph.D. or M.S. with 8+ years in AI research or engineering, specializing in world modeling.
  • Experience building large‑scale simulators and predictive models.
  • Expertise in transformer‑based LLMs and diffusion models.

Responsibilities

  • Define and evolve the overall world model architecture.
  • Oversee planning and manage research engineers for project success.
  • Report project status and champion best practices.

Skills

AI research or engineering experience
World modeling expertise
Simulation knowledge
Generative modeling skills
Leadership and project management

Education

Ph.D. or M.S.
Job description
About the Institute of Foundation Models

We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.

As part of our team, you’ll have the opportunity to work on the core of cutting‑edge foundation model training, alongside world‑class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem‑solving skills will be instrumental in establishing MBZUAI as a global hub for high‑performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers.

The Role

You will own the end‑to‑end strategy, design, and delivery of our general‑purpose world modeling efforts. You’ll translate cutting‑edge research (e.g., the PAN framework) into robust, production‑ready simulators, guide a multidisciplinary team of engineers and scientists, and ensure alignment with IFM’s mission.

Key Responsibilities
Technical Leadership & Vision
  • Define and evolve the overall world model architecture, drawing on the PAN principles:
    1. Multimodal data ingestion
    2. Mixed continuous/discrete representations
    3. Hierarchical generative modeling with an enhanced LLM backbone and diffusion‑based predictors
    4. Generative loss grounded in real observations
    5. Simulation for RL‑based agent training
  • Establish performance, safety, and evaluation benchmarks, driving continuous improvement.
Project & Team Management
  • Oversee planning, resourcing, and timeline for world model projects.
  • Manage research engineers and scientists (e.g., data curators, RL experts, simulator devs) to achieve unified progress.
Cross‑Functional Collaboration
  • Partner with agent, reasoning, and deployment teams to integrate world model outputs into downstream applications (robotics, multi‑turn dialogue, autonomous systems).
  • Liaise with external collaborators (academia & industry) to incorporate the latest advances and tooling.
Governance & Communication
  • Report project status, risks, and key insights to senior leadership and stakeholders.
  • Champion best practices in reproducibility, documentation, and knowledge sharing.
Required Qualifications
  • Ph.D. or M.S. with 8+ years in AI research or engineering, specializing in world modeling, simulation, or generative modeling.
  • Proven track record building large‑scale simulators or predictive models for complex environments.
  • Deep expertise in transformer‑based LLMs, diffusion models, and hierarchical latent representations.
  • Hands‑on experience with reinforcement learning frameworks (policy learning, planning with latent dynamics).
  • Strong leadership skills: project management, cross‑site coordination, and team mentorship.
Preferred Qualifications
  • Experience leading multi‑location technical teams in fast‑paced R&D settings.
  • Published contributions to world model architectures or simulation benchmarks.
  • Track record of taking research prototypes into production systems.
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