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Salary
≈ $120k – $270k per year (Estimated)
Location
In office (New York)
Seniority
Junior · 2+ years exp

Confirmed on the employer's own hiring board on Sep 25, 2026. First seen by Alion on Sep 23, 2026. Google DeepMind scores B on the Alion truth index.

Overview
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Google DeepMind is the artificial intelligence research and engineering division of Alphabet, formed in 2023 by merging the London laboratory founded in 2010 with the Google Brain team. It builds frontier foundation models such as the Gemini family, generative media systems including Veo and Imagen, and scientific tools like AlphaFold, whose protein structure predictions earned a share of the 2024 Nobel Prize in Chemistry. The unit pairs long-horizon research on reinforcement learning and general intelligence with product delivery across Google Search, Workspace, Android and Google Cloud.

About the job

The Alignment and Reliability division investigates and creates auditing frameworks, defensive safeguards, specialized toolsets, and autonomous agents to upgrade GDM’s flagship foundation systems. The mandate for the Research Scientist/Engineer centers on engineering novel heuristic and statistical mechanisms to elevate user-facing architectures. The operating rhythm is swift and deeply team-oriented, anchored by a collective ethos of mutual assistance, resilience, and camaraderie intervening during urgent escalations while shaping next-generation intelligence.

In this role, you will be a technical contributor capable of advancing fresh investigative hypotheses from conception to live release with full lifecycle accountability, balancing experimentation with rapid incident mitigation.

Our group specializes in enhancing the ethical integrity and alignment standards of machine intelligence. We pioneer foundational infrastructure integrated across major downstream surfaces, including our flagship consumer interfaces, developer APIs, and core search platforms.

Artificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Drive innovation and understanding of safety and security jailbreaks, owning the problem and delivering mitigations which can be deployed at scale in partnership with product areas.
  • Develop red and blue teaming methods for frontier GenAI models spanning text-to-text, multimodal, and agentic capabilities, delivering actionable insights and solutions.
  • Explore data, reasoning and algorithmic solutions to make sure Gemini Models are safe, maximally helpful, and work for everyone.
  • Improve Gemini’s adversarial with a focus on high-stakes abuse risks in agentic settings.
  • Develop and execute experimental plans to address known gaps, or construct entirely new capabilities.

Qualifications

Minimum qualifications:

  • PhD degree in Computer Science, a related field, or equivalent practical experience.
  • 2 years of experience in Large Language Model safety or security.

Preferred qualifications:

  • Experience in developing and leveraging agentic workflows around safety, behavior, and alignment.
  • Experience with synthetic data generation pipelines, building evaluations and mitigations for non-verifiable tasks using methods such as LLM-as-a-judge, rubric-based rewards, etc.
  • Experience taking research from concept to product.
  • Experience with collaborating or leading an applied research project.
  • Strong experimental taste with good judgment regarding baselines, ablations, and what is worth testing.
  • Track record of publications at NeurIPS, ICLR, ICML.
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