How to pursue a career in technical AI alignment
This guide, authored by Charlie Rogers-Smith and published in June 2022, helps readers navigate the key decisions involved in pursuing a technical AI alignment career. It covers five primary roles (theoretical and empirical research lead, theoretical and empirical research contributor, and professor), discusses whether to pursue a PhD, and provides learning resources for deep learning, machine learning, and alignment theory. It also outlines funding opportunities such as the Long-Term Future Fund and the Open Phil AI Fellowship.
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Theory of Change
By helping talented individuals navigate the career paths into technical AI alignment research, the guide aims to increase the number and quality of researchers working on reducing AI-related existential risk. Clearer career pathways lower the barrier to entry and reduce time wasted on suboptimal preparation, directing more human capital toward the most impactful roles.
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Details
- Last Updated
- Apr 2, 2026, 10:09 PM UTC
- Created
- Mar 19, 2026, 10:30 PM UTC