Research Scientist, Large Scale Pre-Training Data

Posted 20 Hours Ago
Be an Early Applicant
London, Greater London, England
Senior level
Artificial Intelligence
The Role
As a Research Scientist at Google DeepMind, you will conduct empirical research to validate new ideas, develop intuitions based on data scaling laws, and improve understanding of large scale training dynamics, collaborating closely with various teams.
Summary Generated by Built In

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.


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 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.
  • A PhD in machine learning or closely related field, or similar experience.
  • Experience with distributed systems and large scale deep learning performance optimisation.
  • Experience with running large scale data processing pipelines.

Closing date: Monday, 25th November 4:00pm GMT

Top Skills

Python
The Company
1,218 Employees
On-site Workplace
Year Founded: 2010

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.

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