Overview
In this role you will build advanced classifiers and data pipelines to detect misuse, and own end-to-end evaluation and rapid iteration. You will create cross-context monitoring to identify large-scale attack vectors and deploy data-driven response systems against persistent actors. You will evaluate and secure agentic AI systems through threat modeling and robust mitigations, and advance automated red-teaming and adversarial robustness research. This position sits at the frontier of AI safety and product innovation, with impact across research and production in a mission-driven lab.
Responsibilities
- Build classifiers and data pipelines to detect misuse
- Develop cross-context monitoring and signal aggregation for detecting large-scale attack vectors
- Implement data-driven, semi-automated account-level response systems against malicious actors
- Evaluate and secure agentic AI systems with threat models and testing environments
- Advance red-teaming and adversarial robustness research using multi-turn/agentic attacks
Key requirements
- Bachelor’s degree in Computer Science, Machine Learning, or related technical field, or equivalent practical experience
- 5 years of software development experience including Python
- Experience with research-to-deployment pipeline in frontier AI
- Experience working in a software engineering or research team
- collaboration
- architectural judgement
- problem-solving under uncertainty
- Python
- adversarial ML
- threat modeling
…
