Curated roles
Browse roles focused on reducing risks from advanced AI systems, including alignment research, safety engineering, evaluations and related operations.
357 active roles found.
Senior AI red team role on SEI's AI Security team focused on adversary emulation against AI-enabled systems, developing offensive techniques to improve defender preparedness and AI system security.
Two-year postdoctoral research role on mechanistic interpretability and AI reasoning within an ERC-funded project on explainable and robust automatic fact checking. Relevant as adjacent AI safety work because it studies model internals and reasoning behavior.
Research scientist role on DeepMind's GenAI Safety team focused on production monitoring, automated evaluations, and misuse detection for deployed AI models.
Senior Model Policy role at OpenAI focused on designing policies, taxonomies, and evaluation criteria to keep frontier models safe in biological and chemical dual-use scenarios.
AI security researcher role focused on LLM security capabilities, benchmarks, risk identification, and security frameworks for model iteration.
AI red team engineer role focused on adversary emulation against AI-enabled systems, including the model and its surrounding hardware/software/network stack, to prepare defenders for real-world threats.
Cyber-focused AI red team role evaluating model capabilities, safeguards, and abuse risks in agentic systems, with direct responsibility for safety testing and mitigation recommendations.
Associate role on Faculty’s AI Safety team supporting frontier model evaluations, AI safety red teaming, and delivery of responsible AI projects for government and industry clients.
Technical program management role driving AI safety and safeguards initiatives across deployment environments, including model evaluations, mitigations, abuse detection, monitoring, and readiness for high-impact deployments.
A paid MATS research program role involving a ~20 hour AI safety research project focused on pragmatic interpretability or applied safety, with a detailed write-up of findings.
Research role on OpenAI’s Preparedness team focused on frontier AI safety mitigations, evaluations, red-teaming, and alignment/interpretability methods to make deployed models safer.
Associate role on Faculty’s AI Safety team supporting delivery of frontier model evaluations, AI safety red teaming, and related client projects for government and industry.
Research Scientist focused on interpretability and techniques for understanding and steering large AI models, with explicit connection to making models safer and supporting safe model development.
Operations and program lead for Harvard-MIT AI Safety Workshops and related AI safety community events, supporting AI safety career development and workshop programming rather than doing research directly.
Assistant AI Security Software Engineer focused on AI security research, AI red teaming, adversarial machine learning, and building tools for AI security applications.
Research role on OpenAI’s Chat and Multimodal Safety team focused on multimodal safety research, safety evaluations, post-training, and interventions to ensure frontier models behave safely.
Staff software engineer building web applications and backend systems for AI model evaluation, real-time threat detection, and adversarial red teaming for frontier AI deployments.
Senior full-stack software engineer role building AI model evaluation, threat detection, and adversarial red teaming products for frontier labs.
Machine Learning Engineer focused on AI safety solutions, including adversarial testing, model evaluation, robust inference, and monitoring for secure deployment of AI systems.
Research engineer role focused on AI safety evaluations, interpreting model behavior for misalignment, and implementing controls for autonomous AI deployments.