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.
About the job
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 Learning, Generative AI, LLMs, Ml Pipelines, Evaluation Harnesses, Red-Teaming, Adversarial Testing, Ai Safety, Benchmarks, Prototyping
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