From Google's careers page
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Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Drive an ambitious research agenda in post-training, reinforcement learning, and agentic modeling to improve Gemini's reasoning, tool use, factuality and multimodal performance across global languages, dialects, and locales.
Develop scalable algorithms for cross-lingual capability transfer, synthetic data generation, reward modeling, and self-improvement flywheels that close the quality gap for both major global languages and low-resource languages.
Improve local and cultural grounding, factuality, naturalness, and language consistency across long-horizon multi-turn and multimodal interactions (text, speech, image, and video).
Design trustworthy evaluation methodologies, evaluations, and human-grounded reward signals to measure and steer complex agentic and culturally nuanced model behaviors.
Partner closely with core Gemini post-training, agentic, and pretraining/mid-training teams—as well as product partners across Google—to land research breakthroughs directly into flagship Gemini models.
Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related technical field, or equivalent practical experience.
Experience with research in one or more of the following areas: LLM post-training and alignment, reinforcement learning, multilingual benchmarking, reasoning and agentic systems, or foundation model training.
Experience training, post-training, or evaluating foundation models.
Ability to translate open-ended research ideas into landed improvements in frontier models across multi-team collaborations.
Excellent communication and collaboration skills, and a genuine passion for human languages and building AI that works for people everywhere.
Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related technical field, or equivalent practical experience.
Experience with research in one or more of the following areas: LLM post-training and alignment, reinforcement learning, multilingual benchmarking, reasoning and agentic systems, or foundation model training.
Experience training, post-training, or evaluating foundation models.
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Hi [Name], I just applied for the Research Scientist, Gemini Multilinguality, Google DeepMind role at Google. My background in [your most relevant experience] lines up well with what the team is looking for. Would you be open to a quick chat, or could you point me to the right person on the team? Thank you!
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