Key responsibilities include:

• Post-training/instruction tuning state-of-the-art LLMs, focusing on text-to-text, image/video/audio-to-text modalities and agentic capabilities
• Exploring data, reasoning, and algorithmic solutions to ensure Gemini Models are safe, maximally helpful, and work for everyone
• Improve Gemini's adversarial robustness, with a focus on high-stakes abuse risks
• Design and maintain high-quality evaluation protocols to assess model behavior gaps and headroom related to safety and fairness
• Develop and execute experimental plans to address known gaps, or construct entirely new capabilities
• Drive innovation and enhance understanding of Supervised Fine Tuning and Reinforcement Learning fine-tuning at scale

To succeed as a Research Scientist in the Gemini Safety team, we look for the following skills and experience:

• PhD in Computer Science, a related field, or equivalent practical experience
• Significant LLM post-training experience
• Experience in Reward modeling and Reinforcement Learning for LLMs Instruction tuning
• Experience with Long-range Reinforcement learning
• Experience in areas such as Safety, Fairness, and Alignment
• Track record of publications at NeurIPS, ICLR, ICML
• Experience taking research from concept to product
• Experience with collaborating or leading an applied research project
• Strong experimental taste: Good judgment regarding baselines, ablations, and what is worth testing
• Experience with JAX

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