We are seeking a Research Scientist to drive research in Gemini for information tasks. This role involves working on post-training innovations to improve the quality, groundedness, and factuality of Gemini models in search mode. The successful candidate will contribute to improving helpfulness and factuality of Gemini models, impacting product surfaces including AI Mode, Gemini App, AI Studio, and Vertex AI.
Key responsibilities include researching post-training methods such as reinforcement learning and self-supervised training for information-seeking scenarios in Gemini, developing novel evaluation methods for improving model quality, grounding, and factuality, and researching orchestration of tool calls and improved retrieval methods for information-seeking scenarios.
To succeed in this role, you should have a PhD in a relevant area or an equivalent research/publication record, strong software-engineering skills, and experience in reinforcement learning, post-training methods, and LLMs for information-seeking scenarios.
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