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.

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! 

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.

We’re looking for a number of Research Scientist’s to join our Data team. As a member of this team you will help guide and execute the strategy for human data collection and innovation of new data collection methods. 

Data is central to the advancement of AI research, and as a member of the Data team you will play a key role in improving the range and quality of data used by researchers at Google DeepMind. Your day-to-day work will involve collaborating closely with researchers, as a member of cutting-edge research projects. 

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 cognitive science, human computer interaction, and machine learning, drawing on expertise from a variety of disciplines.

We do not require candidates for this role to have experience with machine learning, but you should be excited to collaborate with people who do!

• Design and implement a range of human data collection tasks for a variety of model evaluation and training objectives. High quality data requires tasks which are carefully designed with both model objectives and human participants in mind. 
• Collaborate with multiple research partners to forge links and develop synergies to boost human data collection quality and efficiency across the company.
• Develop and support analysis tooling to support efficient data quality workflows within the wider team.
• Design, implement, run, and analyse experiments which further our understanding of how to collect and high-quality human data.
• Report and present research findings and developments to internal and external collaborators with effective written and verbal communication

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 data science, cognitive science, or HCI-related disciplines or equivalent practical experience.
• Experience designing, running, and analysing online experiments involving human participants, or data collection for evaluating or training machine learning models.
• A high-level understanding of generative AI - particularly aspects that are relevant to designing data collection tasks.
• Fluency in Python.

In addition, the following would be an advantage:

• Experience with large-scale online data collection.
• Experience with customised UI/survey design to optimise participant experience and data quality.
• Experience with rigorous data quality analysis.
• Hands-on experience of training or evaluating machine-learning models with human data.
• Some familiarity with SQL.

Applications close: Friday 7th June at 5pm BST.