Research Engineer, Frontier Safety Mitigations, DeepMind

Requirements:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Nice to haves:

• PhD in Computer Science, Machine Learning, or equivalent practical experience, or publications at venues (e.g., NeurIPS, ICLR, ICML, or EMNLP).
• Experience with cybersecurity detection and response, building classifiers and anomaly detection systems at scale, taking safety defenses or mitigations from research concepts to scalable production systems.
• Experience in adversarial machine learning, automated red-teaming, or model interpretability and probes.
• Experience collaborating on or leading applied ML projects, including LLM training, inference, and fine-tuning.
• Experience using AI coding agents with strong architectural judgment and with TPUs and JAX.
• Knowledge of AI control, chain-of-thought monitoring, monitorability, and related frontier safety research.

What you'll be doing:

• Build advanced classifiers and data pipelines to detect misuse.
• Build cross-context monitoring systems to detect coordinated harms.
• Implement data-driven, semi-automated account-level response systems.
• Evaluate and secure agentic AI systems.
• Advance research in automated red-teaming and adversarial robustness.

Perks and Benefits:

• Opportunity to work in a dedicated scientific community at DeepMind.
• Work on cutting-edge AI projects with interdisciplinary teams.
• Career advancement opportunities and diverse learning experiences.