The Role
As a member of the Diffusion LLM Team at MBZUAI, you will play a central role in designing, building, and releasing industrial-scale Diffusion Large Language Models. Our team has two core missions. First, we develop and release diffusion-based LLMs that push the speed-quality frontier at scale by matching autoregressive model quality while enabling faster generation. Second, we improve inference-time scaling relative to standard LLMs, so that additional test-time compute translates into higher-quality samples.
You will work closely with researchers and engineers across architecture, training, and infrastructure to turn research ideas into high-impact model releases for next-generation LLMs.
Key Responsibilities
- Design, train, and scale large language models for research and real-world deployment.
>- Lead or contribute to the release of industrial-scale diffusion language models.
>- Develop and evaluate training strategies and objectives for efficient model scaling.
>- Publish research findings and contribute to open-source model and code releases.
>
Academic Qualifications
MSc or PhD in Machine Learning or Computer Science, or equivalent industry experience.
Professional Experience
- Hands-on experience training large models using modern deep learning frameworks at scale.
>- Strong background in transformer architectures and large-scale optimization techniques.
>- Demonstrated expertise in LLM pre-training or post-training, with a strong focus on model scaling.
>- Research track record evidenced by publications, open-source contributions, or released models.
>- Knowledge of diffusion models or discrete diffusion methods is a plus, but not required.
>- Ability to work independently while contributing effectively to a collaborative research team.
>
