Applications close Friday 2nd June at 5pm
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About usAt Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Safety research at Google DeepMind aims to identify potential risks from developing AGI, and develop technical approaches to address them. As a Research Engineer, you will design, implement, and empirically validate algorithms that promote safety.
Conducting research into any transformative technology comes with the responsibility to build mechanisms for safe and reliable development and deployment at every step. Technical safety research at Google DeepMind investigates questions related to alignment, evaluations, reward design, interpretability, robustness, and generalisation in machine learning systems. Proactive research in these areas is essential to the fulfilment of the long- term goal of Google DeepMind Research: to build safe and socially beneficial AI systems.
Research on technical AI safety draws on expertise in deep learning, statistics, human feedback, and more. Research Engineers work on the forefront of technical approaches to designing systems that reliably function as intended while discovering and mitigating risks, in close collaboration with other AI research groups within and outside of Google DeepMind.
The roleSafety Research Engineers at Google DeepMind work directly on a wide range of conceptual, theoretical and empirical research projects, typically in collaboration with Research Scientists. You will apply your engineering and research skills to accelerate research progress through developing prototypes, designing and scaling up algorithms, overcoming technical obstacles, and designing, running, and analysing experiments.
Competitive salary applies.
Closing date : 2 June 2023