Lead AI Safety & Alignment Research Scientist

AI Breaking Wire

Greater London

Hybrid

GBP 90,000 - 150,000

Full time

13 days ago
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Benefits offered by this job

Equity / stock options
Health, wellness & family care
World-class computing resources
Generous sabbatical and time-off

Job summary

Google DeepMind is seeking an AI Safety and Alignment Researcher to develop rigorous empirical and theoretical frameworks that keep advanced AI systems safe, robust, and aligned with human values.

The role focuses on foundational and applied research across model interpretability, robustness, and scalable oversight, with strong ties to product and engineering teams to embed safety into deployments.

Qualifications

  • PhD (preferred) in a quantitative field with strong research track record.
  • Strong background in ML safety, alignment, interpretability, or adversarial robustness.
  • Proficiency in Python and deep learning frameworks (TensorFlow or PyTorch).
  • Excellent communication skills with peer-reviewed publications.

Responsibilities

  • Conduct fundamental and applied research into model interpretability, robustness, and scalable oversight.
  • Design evaluation benchmarks to test model vulnerabilities against jailbreaks, prompt injection, and deceptive alignment.
  • Partner with product and engineering teams to integrate safety guardrails into deployment pipelines.
  • Collaborate with academic institutions and external research bodies on safety standards.

Skills

ML safety
Interpretability
Adversarial robustness
Academic publishing

Education

PhD in CS/Math/Physics/Philosophy

Tools

TensorFlow
PyTorch

Job description

Google DeepMind is seeking an AI Safety and Alignment Researcher to develop rigorous empirical and theoretical frameworks that keep advanced AI systems safe, robust, and aligned with human values.

The role focuses on foundational and applied research across model interpretability, robustness, and scalable oversight, with strong ties to product and engineering teams to embed safety into deployments.

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