Member of Technical Staff - AI Safety

- Leverage expertise to uncover potential risks and develop novel mitigation strategies, including data mining, prompt engineering, LLM evaluation, and classifier training. - Create and implement comprehensive evaluation frameworks and red-teaming methodologies to assess model safety across diverse scenarios, edge cases, and potential failure modes. - Build automated safety testing systems, generalize safety solutions into repeatable frameworks, and write efficient code for safety model pipelines and intervention systems. - Maintain a user-oriented perspective by understanding safety needs from user perspectives, validating safety approaches through user research, and serving as a trusted advisor on AI safety matters. - Track advances in AI safety research, identify relevant state-of-the-art techniques, and adapt safety algorithms to drive innovation in production systems serving millions of users. - Embody our culture and values.