Research Scientist, Gemini Diffusion

We are looking for a Research Scientist to join our team in London and help us accelerate our mission. As a Research Scientist, you will apply your deep scientific knowledge and research skills to advance paradigm-shifting research at a large scale. You will be at the heart of our efforts to deliver step-changes in the capabilities of our frontier models, with a significant focus on our Gemini Diffusion project. You will work in a tight-knit and highly collaborative team environment that fosters fundamental research and technical innovation, giving you hands-on experience with improving state-of-the-art AI systems. As a team member, your work may involve:

• Brainstorming new disruptive ideas that could become the next generation of frontier AI models, particularly within the text diffusion space.
• Prototyping and developing these ideas with the rest of the team, contributing directly to Gemini Diffusion research.
• Solving key research challenges by designing and executing experimental research on text diffusion models, sharing analyses, and proposing next steps.
• Rigorously validating the theoretical and practical impact of our work at a large scale.
• Working collaboratively with other Generative AI teams to move the technologies we develop out of the lab and into production.
• Advancing the fundamental architecture, algorithmic design, and capabilities of large-scale diffusion models.
• Bringing deep scientific expertise into our projects. You will share your insights and knowledge with other researchers and engineers. We take scientific rigor seriously, and you will be a steward of that ethos.

• Advanced degree in computer science, electrical engineering, science, mathematics, or equivalent experience.
• Academic research experience in machine learning, publications, or research experience in related fields.
• Experience with some or all LLMs, Transformers, Diffusion models, Text diffusion, Large-scale distributed training.
• Strong communication skills (via discussion, presentation, technical and research writing, whiteboarding, etc.).
• Programming experience, particularly with Python-based scientific libraries such as Numpy, Scipy, JAX, PyTorch, or TensorFlow.
• Deep familiarity with the machine learning, mathematics, and statistics needed to follow relevant research papers (linear algebra, calculus, etc.) and reason about cutting-edge innovations.
• Agile and solution-focused mindset - be prepared to work on anything!

• A track record of building software, either in open source or as part of a company product or research papers.
• Large-scale system design, distributed systems.
• Distributed computation for ML, especially in the context of accelerators (e.g., sharding, multi-host computation).
• C++ or broader programming experience.
• Data engineering and visualisation.