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AnthropicAnthropicSan Francisco, CA

ML/Research Engineer, Safeguards

Build ML systems to detect and mitigate AI misuse, including classifiers for anomalous behavior, multi-exchange harm monitoring, and agentic safety evaluations. Requires 4+ years ML experience, Python proficiency, and research-to-deployment skills.

350k – 500k/yr
Hybrid4+ YOEML Engineering

About the role

Responsibilities

  • Develop classifiers to detect misuse and anomalous behavior at scale. This includes developing synthetic data pipelines for training classifiers and methods to automatically source representative evaluations to iterate on
  • Build systems to monitor for harms that span multiple exchanges, such as coordinated cyber attacks and influence operations, and develop new methods for aggregating and analyzing signals across contexts
  • Evaluate and improve the safety of agentic products—developing both threat models and environments to test for agentic risks, and developing and deploying mitigations for prompt injection attacks
  • Conduct research on automated red-teaming, adversarial robustness, and other research that helps test for or find misuse

You may be a good fit if you

  • Have 4+ years of experience in ML engineering, research engineering, or applied research, in academia or industry
  • Have proficiency in Python and experience building ML systems
  • Are comfortable working across the research-to-deployment pipeline, from exploratory experiments to production systems
  • Are worried about misuse risks of AI systems, and want to work to mitigate them
  • Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders

Strong candidates may also have experience with

  • Language modeling and transformers
  • Building classifiers, anomaly detection systems, or behavioral ML
  • Adversarial machine learning or red-teaming
  • Interpretability or probes
  • Reinforcement learning
  • High-performance, large-scale ML systems

Annual Salary: $350,000—$500,000 USD

Skills

PythonMachine LearningTransformersClassifiersAnomaly DetectionAdversarial Machine LearningRed-TeamingInterpretabilityReinforcement LearningLarge-Scale Ml Systems

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