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SnapshotWe’re looking for engineers and scientists to help accelerate our research in Artificial Intelligence as part of our mission to create the next generation of Generative AI technologies. Our team has a unique mandate: to work on speculative, longer-horizon research projects that, if successful, yield step-change improvements in the capabilities of our frontier models. We target paradigm-shifting ideas and are prepared to invest the time and resources necessary to achieve them. Our goal is to ideate, research, develop, validate, and integrate these improvements into major Google technologies.
Our primary research focus is Gemini Diffusion, our state-of-the-art text diffusion model. We believe that text diffusion has the potential to unlock a new paradigm in generative AI, offering unprecedented capabilities and lightning-fast latency. With strong backing from GDM leadership, our team is dedicated to thoroughly exploring and advancing this technology.
Our team is a multi-disciplinary group of engineers and scientists that work in close collaboration, leveraging our unique skills with a strong focus on building and shipping ground-breaking AI. We are a problem-focused team, meaning we are interested in any tool or idea that can solve a concrete problem, rather than being tied to a particular set of tools.
About usArtificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
The roleWe 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.
We take a holistic view of people's backgrounds and do not expect you to be an expert in all areas. We invest heavily in training and development, and continual learning is a key part of the role. In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:
- 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!
We're also interested in any of:
- 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.
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