AI Safety Jobs

Manage cloud infrastructure for open-source LLM evaluation tooling, focusing on evaluating ML model capabilities and alignment.

The role focuses on building frameworks for evaluating AI models and improving their performance through robust data pipelines and automation.

The Staff Software Engineer, Data Platform role focuses on designing and developing data platforms that support AI safety and alignment through human evaluation and reinforcement learning.

The role involves creating and optimizing deep learning architectures with a focus on AI safety methods for sensor fusion in autonomous driving.

Intern role focused on creating social media and video content about AI safety and biosecurity.

The role involves managing workspace and logistics for AI safety research programs, organizing events for researchers, and overseeing daily operations.

Facilitator role focused on developing talent in AI safety through discussion-based learning and mentorship.

Fellowship focused on research in AI security and technology policy at RAND Corporation.

Expression of interest in future openings at Harmony Intelligence, an AI safety research and engineering company focusing on catastrophic risk evaluations and red-teaming.

Research positions focused on AI safety, security, and alignment within the COMPASS research group at the ELLIS Institute Tübingen.

The Technical Director, AI Safety will lead the technical strategy for AI safety, manage an R&D team, and shape safety solutions and policy.

The Research Scientist role involves solving research problems related to AI evaluation, robustness, and red teaming of language models.

This role invites individuals to engage in research on AI model threats, participate in evaluations, and influence AI policy initiatives.

Internship focused on developing a reliability platform for LLM applications, including safety testing and verification of AI models.

The role focuses on building a platform for training and evaluating interpretable AI systems, emphasizing safety and reliability.

The role involves designing and implementing ML models to address advanced AI safety challenges, collaborating with researchers, and developing evaluation frameworks.

The role involves developing and evaluating probabilistic inference methods to support safe-by-design AI systems.

PhD research position focused on AI safety, investigating large language models and evaluating AI systems to ensure safe development.

Lead AI safety research and conduct red teaming for frontier models in sensitive domains.

Lead Faculty's AI safety research team, focusing on safe AI systems and conducting research on large language models.