Responsibilities
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.
Qualifications
Required Qualifications
- Bachelor’s Degree in Computer Science, or related technical discipline AND technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python