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As a Research Engineer on the Sociotechnical Analysis of Model Behaviour (SAMBA) team, you will conduct cutting edge research on model behaviours that impact people and society. You will work closely with Research Scientists on the team to conduct and operationalize research on model behaviour relevant to Responsible AI. As part of your work, you will be responsible for building out frontier evaluations of model behaviour and helping to integrate them into existing infrastructure.

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.

You will contribute to empirical and conceptual research that helps to identify and define appropriate model behaviour in context. You will work closely with Research Scientists to transform research findings into concrete, measurable metrics and systematic evaluations. This position is a 12 month, fixed-term contract.

• Contribute to research design to conduct experiments on model behaviour
• Automate and improve performance of evaluation processes
• Build and maintain evaluation pipelines
• Perform data analysis to synthesise and visualise research findings and evaluation results
• Contribute to research publications

You are a Research Engineer who is interested in applying your skills to better under model behaviour in areas with large impacts on people and society. You are passionate about evaluation and quantification and able to work with technical teams to integrate your work into existing platforms and infrastructures.

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• A masters or equivalent experience in Computer Science, ML,  Data Science, or similar technical field
• Strong programming skills: Proficiency in Python (with experience in relevant libraries like Pandas, NumPy, Scikit-learn) or other scripting languages.
• Solid understanding of statistical concepts, and ability to perform basic data analysis and visualization
• Experience with or an interest in AI evaluation: familiarity with designing and conducting evaluations of AI models, applying benchmarks, etc.
• Good communication and collaboration skills: an ability to effectively communicate and work with researchers from a wide variety of backgrounds, including non-technical backgrounds
• Comfortable working in a fast-paced environment 

In addition, the following would be an advantage: 

• A history of high quality research, touching on topics relevant to responsible AI

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