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Research Engineering Manager, Responsible Frontier AI Research, DeepMind

Google
London, GBR
Manager
Onsite
Discovered 6 days ago

Full Job Posting

Responsibilities

  • Set and communicate priorities for multiple workstreams that support the broader responsibility organization's goals. Align strategy, processes, and decision-making across teams, and move engineering capacity between research projects as priorities change.
  • Set clear expectations with individuals, including tech leads, based on their level and role. Meet regularly to discuss performance and development, provide feedback and coaching, and hire and grow a high-performing team.
  • Develop the long-term technical goal and roadmap within, and often beyond, the scope of your teams, covering systems such as evaluation pipelines, red-teaming tools, autoraters, and mitigation training pipelines. Evolve it as frontier models become more capable, agentic, and multimodal.
  • Oversee system designs and review code to solve ambiguous problems. Set best practices for code quality, scalability, reliability, and secure handling of sensitive data.
  • Partner with Research Scientists, Subject-Matter Experts, and Product, Program, Policy, and Trust and Safety teams to turn research into evaluations and mitigations that inform model launch decisions. Present trade-offs and results to senior leadership.

Minimum qualifications:

  • Experience leading teams working on AI safety, security, or responsible AI research (e.g., adversarial robustness, red teaming, safety evaluations, or mitigation's for frontier models).
  • Experience with one or more of the following: automated red teaming or jailbreak discovery, LLM-based autoraters and evaluation design, safety classifiers or probes, prompt injection and agent security, or evaluation of severe-harm risks such as CBRN or Harmful Manipulation.

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field with a focus on adversarial machine learning or AI/ML security.
  • Track record of research or engineering achievements, such as publications in peer-reviewed venues, open-source projects, or public benchmarks.

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