Research Scientist/Engineer, Autonomous Security, DeepMind

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA; San Francisco, CA, USA.

Minimum Qualifications: PhD in Computer Science, Cybersecurity, ML, a related field, or equivalent practical experience. 4 years of experience in Python and ML frameworks (PyTorch, JAX, or TensorFlow) training, fine-tuning, and evaluating foundation models. 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, execution-feedback reinforcement learning, and multi-step trajectory reward modeling.

Preferred Qualifications: Experience architecting autonomous agent systems, focusing on multi-step planning, tool orchestration, reward modeling, and reinforcement learning. Experience building scalable simulated execution environments, evaluation harnesses, or synthetic data pipelines for training and benchmarking foundation models. Deep domain expertise in one or more specialized cybersecurity areas, such as vulnerability discovery and automated patching, offensive security operations (red teaming), or advanced threat detection. Track record of published research at ML or cybersecurity venues, or a demonstrated history of deploying AI systems in production security environments.