The Research Scientist/Engineer role at DeepMind focuses on advancing autonomous security through innovative research and development. The team is dedicated to solving complex global challenges using artificial intelligence, with an emphasis on cybersecurity applications. This position involves designing methodologies for training and evaluating machine learning models, particularly in the context of security. The role also includes contributing to the research community by publishing findings and collaborating with academic institutions.

• PhD in Computer Science, Cybersecurity, ML, or a related field, or equivalent practical experience.
• 4 years of experience in Python and ML frameworks such as PyTorch, JAX, or TensorFlow.
• 3 years of experience applying ML or automated reasoning to cybersecurity, systems, program analysis, or code generation.
• 2 years of experience in LLM post-training, including supervised fine-tuning and reinforcement learning.

• Design and iterate on post-training methodologies for Gemini, including reinforcement learning from execution feedback.
• Build scalable simulated environments and synthetic data pipelines for complex security workflows.
• Architect autonomous agent harnesses capable of multi-step planning and decision-making under adversarial conditions.
• Develop end-to-end evaluation benchmarks for measuring capability limits across security tasks.
• Transition research innovations into Google's internal defenses and customer products.

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.