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Brave is seeking an AI Security Researcher to help mitigate security risks in AI systems, particularly LLM-powered web agents and chatbots. You will design and execute adversarial evaluations to uncover failure modes such as prompt injection, tool abuse, and data exfiltration. Your work will involve analyzing model behavior to understand and forecast security risks in frontier models, developing security-focused training and fine-tuning techniques, and augmenting web agents with security principles including information flow control and privilege control.
You will partner with engineers and privacy, ML, and cryptographic researchers to translate security findings into product changes, tests, and measurable improvements. A key part of this role is helping define Brave's forward-looking security strategy and policy for building and responsibly releasing web agents, with a focus on user protection.
Ideal candidates have demonstrated experience in Secure AI and prompt injection attacks, a strong publication record in AI security or ML security, and a track record of shipping products in fast-moving environments. You should have strong Python coding skills, familiarity with ML frameworks like PyTorch or JAX, and deep experience training, fine-tuning, and evaluating large language models. Experience applying security principles such as information flow control and access control is essential. A Ph.D. in computer science is highly preferred, though exceptions may be considered for candidates with strong industry experience.
Skills that set candidates apart include knowledge of AI systems pipelines and security evaluation, open-source security/privacy projects, experience with confidential computing and ZKP/SMPC protocols, and a strong publication record in premier systems or ML venues. Brave is a well-funded international startup headquartered in San Francisco, offering competitive compensation, cutting-edge technology, and significant room for personal growth.
