Research Engineer - The Diffusion LLM Team

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

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.
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• $150,000 - $400,000 a year
• Salary Range
• The posted salary range represents the company’s good faith estimate of the
• compensation for this position upon hire. The actual compensation offered may
• vary within this range depending on individual qualifications, including but not
• limited to relevant skills, experience, education, certifications, geographic
• location, and specific business needs.
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