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Snapshot
At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. We are seeking a highly motivated Research Scientist to join our team and contribute to groundbreaking fundamental research and deployment in large scale pre-training.
About Us
Artificial 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 Role
We’re looking for a Research Scientist with a strong empirical and theoretical understanding of deep learning with a focus on data, as well as strong engineering skills and understanding of distributed systems.
Key responsibilities:
- Conduct careful empirical research to validate novel research ideas to improve performance of Gemini models.
- Develop strong intuitions grounded in data scaling laws and theoretical insights that can lead to research breakthroughs and new model capabilities.
- Dive deep into specific areas of the pre-training stack to improve our understanding of large scale training dynamics.
- Collaborate with the wider Gemini team, engaging closely with the Model, Infrastructure and the Post-Training teams.
About You
In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:
- A PhD in machine learning or closely related field, or similar experience.
- A proven track record of large scale deep learning research with hands-on experience with Python and neural network training (publications, open-source projects, relevant work experience, …).
- An in-depth knowledge of large scale training dynamics.
- Ability to communicate technical ideas effectively, e.g. through discussions, whiteboard sessions, written documentation.
In addition, the following would be an advantage:
- Experience with large scale data processing pipelines.
- Experience with distributed systems and large scale deep learning performance optimisation.
- Experience with running large scale data processing pipelines.
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What We Do
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. Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI). Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges. We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.
