In line with the Seoul Declaration for Safe, Innovative and Inclusive AI from the 2024 AI Seoul Summit, the Korea AI Safety Institute, in collaboration with global AI safety networks and top domestic and international experts, will:
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Take the lead in AI safety policy
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Serve as a hub for conducting experiments and analysis to enhance AI safety and introduce the latest technologies to Korea
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Conduct research to predict and respond to new risks that may arise with the development of AI technology
For detailed information on recruitment, please refer to the Electronics and Telecommunications Research Institute (ETRI) recruitment webpage (https://etri.recruitment.kr/appsite/company/index).
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What we look for
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Our goal is to establish a scientific foundation for understanding AI safety, develop systematic management strategies, and advance research to mitigate AI risks.
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We highly value collaboration, innovation, and diversity and seek responsible and passionate talent eager to work in a dynamic environment with global impact.
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We welcome not only AI-specialized experts but also professionals with relevant experience across various domains, including AI safety management and software framework development.
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Who we’re looking for
The Korea AI Safety Institute seeks individuals with the following competencies and experiences:
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Development of policies and guidelines to make AI models and systems safer and more trustworthy
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Research on global AI ethics and guidelines
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Expertise in AI safety frameworks and evaluations, with a solid understanding of and experience in developing system development methodologies across various domains, including safety-critical software, nuclear systems, and healthcare
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Understanding of the latest LLM utilization methodologies or technical approaches (e.g., Chain of Thought, Retrieval-Augmented Generation)
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Experience in benchmarking and testing the performance of LLMs
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Experience in safety validation prompting techniques and handling security attacks (e.g., Jailbreak, Red Team)
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Research on advanced AI fields (e.g., machine learning, optimization techniques, LLMs, generative models, reinforcement learning)
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English proficiency for engaging in technical discussions
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