Research Scientist, Safe, Reliable & Trustworthy AI

DeepMind
May 26, 2023
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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 opportunities 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. Our special interdisciplinary team combines the best techniques from deep learning, reinforcement learning and systems neuroscience to build general-purpose learning algorithms. We have already made a number of high profile breakthroughs towards building artificial general intelligence, and we have all the ingredients in place to make further significant progress over the coming year!

About us

Google DeepMind is a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit. The team you'd join collaborates with engineers and research scientists to enable safe, reliable and trustworthy AI.

We've built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don't set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.

We constantly iterate on our workplace experience with the goal of ensuring it encourages a balanced life. From excellent office facilities through to extensive manager support, we strive to support our people and their needs as effectively as possible

We offer many benefits and we're happy to discuss this further throughout the interview process.

The role

Your main focus will be on ensuring that future AI systems are robust, fair and are thoroughly evaluated against a wide range of threat models. You will be part of a team developing safe, reliable and trustworthy AI for the real world.

Research Scientists at Google DeepMind lead our efforts in developing novel algorithmic architecture towards the end goal of solving and building Artificial General Intelligence. Having pioneered research in the world's leading academic and industrial labs in PhDs, post-docs or professorships, Research Scientists join Google DeepMind to work collaboratively within and across Research fields. They develop solutions to fundamental questions in machine learning, computational neuroscience and AI.

Drawing on expertise from a variety of disciplines including deep learning, reinforcement learning, computer vision, language, neuroscience, safety, control, robotics and multi-agent, our Research Scientists are at the forefront of groundbreaking research.

Key responsibilities

  • Design, implement and evaluate models, agents and software prototypes of perceptual processing.
  • Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing.
  • Suggest and engage in team collaborations to meet ambitious research goals.
  • Work with external collaborators and maintain relationships with relevant research labs and key individuals as appropriate.
  • 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:

  • PhD in a technical field or equivalent practical experience.
  • Research experience in a relevant field.
  • Experience of a multi-paradigm language such as Python and working knowledge of JAX, Tensorflow, PyTorch, or a similar machine learning framework.
  • In addition, the following would be an advantage:

  • Relevant experience to the position such as post doctoral roles, a proven track record of publications, or deep neural network architectures.
  • Experience in reliability of neural networks, for example: adversarial robustness, safety, fairness.
  • Strong engineering skills and experience in collaborative software development, either open-source or proprietary.
  • Experience in deploying ML models at scale.
  • Competitive salary applies.

    Closing date: Friday 26th May at 5:00pm BST

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