Research Scientist/Engineer, Autonomous Security, DeepMind

What you'll do

• Design post-training methods for Gemini, including supervised fine-tuning and reinforcement learning from execution feedback.
• Build simulated environments, synthetic data pipelines, and autonomous agent systems for complex security workflows.
• Develop evaluations for security capabilities and transfer research into products, reports, and publications.

What they ask for

• PhD in Computer Science, Cybersecurity, ML, a related field, or equivalent practical experience.
• 4 years of experience with 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.

Nice to have

• Experience architecting autonomous agent systems or building scalable simulated environments, evaluation harnesses, or synthetic data pipelines.
• Cybersecurity expertise, relevant research publications, or a history of deploying AI systems in production security environments.

Pay

$174000 - $252000 (USD) base salary

Tools

Python, PyTorch, JAX, TensorFlow, Gemini

AI focus

AI research and engineering for autonomous cybersecurity agents, including foundation-model post-training, reinforcement learning, reward modeling, synthetic data generation, and security evaluation.