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Scale AI

Research Scientist, Frontier Risk Evaluations

Designs evaluation measures, harnesses, and datasets to assess risks from frontier AI systems, including dangerous capabilities testing. Collaborates with agencies, publishes methodologies for policymakers; requires 3+ years ML experience and publications in generative AI.

197k – 247kSan Francisco, CANew York, NYSeattle, WAAI ResearchOnsite3+ YOE
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About the role

Responsibilities

  • Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities.
  • Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems.
  • Publish evaluation methodologies and write technical reports for policymakers.

Requirements

  • Commitment to promoting safe, secure, and trustworthy AI deployments.
  • Practical experience conducting technical research collaboratively, including building and instrumenting ML pipelines, writing evaluation harnesses, and prototyping ideas from research literature.
  • Track record of published research in machine learning, particularly generative AI.
  • At least three years of experience addressing sophisticated ML problems in research or product development.
  • Strong written and verbal communication skills for cross-functional teams.

Nice to Have

  • Experience crafting evaluations and benchmarks, or background in data science roles related to LLM technologies.
  • Experience with red-teaming or adversarial testing of AI systems.
  • Familiarity with AI safety policy frameworks (e.g., NIST AI RMF, EU AI Act, Korea AI Basic Act).

Skills

Machine LearningGenerative AILLMsMl PipelinesEvaluation HarnessesRed-TeamingAdversarial TestingAi SafetyBenchmarksPrototyping

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