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Research Engineer / Scientist (Alignment)

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Onsite

Research Engineer / Scientist (Alignment)

Anthropic

Research Engineer / Scientist (Alignment)

Skills

Machine LearningAIKubernetesNLP / Natural Language Processing

2 months ago

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Important information


Contract type:

Permanent

Salary:

$350,000 – $500,000 / year

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

21 October 2026

What they need


  • As a Research Engineer on Alignment Science, you’ll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team
  • Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. Our current topics of focus include..
  • Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains
  • AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios
  • Alignment Stress-testing: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise
  • Automated Alignment Research: Building and aligning a system that can speed up & improve alignment research
  • Representative projects:
  • Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions
  • Run multi-agent reinforcement learning experiments to test out techniques like AI Debate
  • Build tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks
  • Write scripts and prompts to efficiently produce evaluation questions to test models’ reasoning abilities in safety-relevant contexts
  • Contribute ideas, figures, and writing to research papers, blog posts, and talks
  • Run experiments that feed into key AI safety efforts at Anthropic, like the design and implementation of our Responsible Scaling Policy

Benefits

  • Comprehensive health, dental, and vision insurance for you and your dependents

  • Inclusive fertility benefits via Carrot Fertility

  • 22 weeks of paid parental leave

  • Flexible paid time off and absence policies

  • Mental health support for you and your dependents

  • Competitive salary and equity packages

  • Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant

  • Retirement plans with competitive matching

  • Life and income protection plans

  • $500/month flexible wellness and time saver stipend

  • Commuter benefits

  • Annual education stipend

  • Home office stipends

  • Relocation support for those moving for Anthropic

  • Daily meals and snacks in the office

  • You could describe yourself as both a scientist and an engineer

  • You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities

  • You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems

  • Pick up slack, even if it goes outside your job description

  • Care about the impacts of AI

  • Prefer fast-moving collaborative projects to extensive solo efforts

  • Have significant software, ML, or research engineering experience

  • Have some familiarity with technical AI safety research

  • Have some experience contributing to empirical AI research projects

  • Have experience authoring research papers in machine learning, NLP, or AI safety

  • Have experience with LLMs

  • Have experience with reinforcement learning

  • Have experience with Kubernetes clusters and complex shared codebases

  • Education requirements: We require at least a Bachelor’s degree in a related field or equivalent experience

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