Researcher, Frontier Cybersecurity Risks
$295,000–$445,000 year
On-siteSan Francisco, California, United States
Job Summary
Design and implement mitigation components for model-enabled cybersecurity misuse, spanning prevention, monitoring, detection, and enforcement under senior leadership guidance. Integrate safeguards across product surfaces with engineering and product teams to ensure protections are consistent, low-latency, and scalable. Evaluate technical trade-offs within the cybersecurity risk domain and propose pragmatic, testable solutions. Collaborate with risk and threat modeling partners to align mitigation design with anticipated attacker behaviors and high-impact misuse scenarios. Execute rigorous testing and red-teaming workflows to stress-test the mitigation stack against evolving threats, then iterate based on findings.
Required Qualifications
- demonstrated experience in deep learning and transformer models
- proficiency with frameworks such as PyTorch or TensorFlow
- strong foundation in data structures, algorithms, and software engineering principles
- familiarity with methods for training and fine-tuning large language models, including distillation, supervised fine-tuning, and policy optimization
- significant experience designing and deploying technical safeguards for abuse prevention, detection, and enforcement at scale
Desired Qualifications
- background knowledge in cybersecurity or adjacent fields
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