A weekly digest of AI safety, governance, policy and responsible AI roles.
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618 active roles found
The AI Governance Advisor role involves building and delivering AI governance training, supporting customers in defining their AI governance roadmap, and managing customer engagements to ensure responsible AI practices.
Senior policy lead for OpenAI’s state and local government engagement on AI-related homeland security, public safety, and responsible deployment/governance issues.
Teacher role for an in-person bootcamp focused on technical AI safety instruction, facilitation, and curriculum development.
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Technical AI safety role focused on full-stack alignment research, including compute-intensive engineering and conceptual work on pretraining and alignment interventions.
The role involves developing hardware architectures for verifying and securing advanced AI systems, collaborating with AI safety researchers, and translating AI security requirements into hardware implementations.
Program management role supporting an AI safety research extension program for fellows, with coordination, operations, workshops, and outcome tracking.
The role involves building safety systems and infrastructure for AI-driven media experiences, focusing on real-time content moderation, risk detection, and ensuring responsible deployment of generative media.
The Technical Threat Investigator role involves conducting investigations into threats targeting OpenAI's models and products, focusing on identifying and disrupting misuse and ensuring compliance and safety in AI operations.
PhD studentship researching LLM safety via mechanistic interpretability, behavioral research, deceptive behavior detection, and inference-time monitoring to reduce model risk.
Project Coordinator supporting a CNAS initiative on AI security and stability, with responsibilities in project management, research support, and policy development related to AI risks and governance.
Hands-on solution engineering role implementing compliant AI governance setups for customers, with explicit focus on AI governance, transparency, compliance, and AI risk frameworks.
Lead data governance for AI training and evaluation data, including provenance, DPIAs, compliance controls, audit evidence, and regulatory readiness for shipped models.
Principal full-stack engineer building an open source LLM research platform and evaluation tools for researchers to evaluate and understand model behavior.
The role involves designing and implementing safety alignment techniques for AI systems, creating datasets for safety alignment, and building infrastructure for safety evaluations.
The role involves leading the SPAR program, the largest AI safety research fellowship, focusing on strategic expansions, managing research managers, and cultivating relationships with AI safety researchers.
Head of Talent Operations for an AI safety fieldbuilding organization, combining recruiting, ecosystem headhunting, grantmaking, and partnerships to support the AI safety talent pipeline.
Research manager for SPAR, an AI safety research fellowship, supporting mentors and mentees, program operations, and events for an AI safety fieldbuilding organization.
In this role, you'll build out a talent database for AI safety organizations to coordinate on talent, contributing to mitigating risks from advanced AI.
Governance research role focused on frontier AI governance, risk management, loss of control, and internal deployment of advanced AI systems.
The role involves building front-end interfaces for an open source LLM evaluation platform, which is relevant to AI safety as it aids in the evaluation of AI models.