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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 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. Our team is responsible for enabling AI systems to reliably work as intended, including identifying potential risks from current and future AI systems, and conducting technical research to mitigate them. As a Research Engineer, you will design, implement, and empirically validate approaches to alignment and risk mitigation, and integrate successful approaches into our best AI systems. Conducting research into any transformative technology comes with responsibility to build mechanisms for safe and reliable development and deployment at every step. Technical safety research at Google DeepMind investigates questions related to evaluations, reward learning, fairness, 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: to build safe and socially beneficial AI systems.
