Research Scientist, Gemini Agent Safety, DeepMind

• Design, implement, and maintain high-quality protocols to identify safety gaps in model behavior across all Gemini and GenAI models, and feed these insights back into the post-training process to continuously improve both in-model and out-of-model protection.
• Explore, adapt, and apply innovative modeling and alignment techniques to solve real-world safety and alignment challenges under tight launch timelines.
• Drive innovation in model optimization, advancing the application of Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) techniques at massive scale.
• Partner closely with post-training, evaluation, and product teams to align incentives, close safety gaps, and influence safety decisions without direct authority.

Minimum qualifications:

• PhD in Computer Science, a related field, or equivalent practical experience.
• 1 year experience with Generative AI, Large Language Models, natural language processing, or Agent-based systems.

Preferred qualifications:

• Experience in AI safety and model alignment.
• Experience developing AI agents, safety-critical systems, or Machine Learning Infrastructure.
• Expertise in reward modeling, Reinforcement Learning (RL) for LLMs, instruction tuning, and long-range RL.
• Ability to drive research concepts to product realization with a strong track record of engineering abilities and experimental work.
• Track record of publications at AI/ML venues (e.g., NeurIPS, ICLR, ICML, EMNLP, AAAI, UAI).

• PhD in Computer Science, a related field, or equivalent practical experience.
• 1 year experience with Generative AI, Large Language Models, natural language processing, or Agent-based systems.