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.

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.

- 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.