Anthropic AI Safety Fellow at Anthropic in San Francisco Bay Area

Summary: Anthropic is a public benefit corporation dedicated to creating reliable and beneficial AI systems. They are seeking individuals for their Anthropic Fellows Program, aimed at accelerating AI safety research through mentorship and funding for empirical projects over a four-month period. Responsibilities: - Use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission) - Undergo a project selection & mentor matching process - Work on AI safety research areas, such as Scalable Oversight, Adversarial Robustness and AI Control, Model Organisms, Model Internals / Mechanistic Interpretability, and AI Welfare Required Qualifications: - Are motivated by reducing catastrophic risks from advanced AI systems - Are excited to transition into full-time empirical AI safety research and would be interested in a full-time role at Anthropic - Have a strong technical background in computer science, mathematics, physics, cybersecurity, or related fields - Thrive in fast-paced, collaborative environments - Can implement ideas quickly and communicate clearly - Fluent in Python programming - Available to work full-time on the Fellows program for 4 months - Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience - Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience - Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position - Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program Preferred Qualifications: - Experience with empirical ML research projects - Experience working with Large Language Models - Experience in one of the research areas mentioned above - Experience with deep learning frameworks and experiment management - Track record of open-source contributions Required Skills: Python programming, Empirical machine learning research, Large Language Models, Deep learning frameworks, Experiment management, AI safety research, Computer science, Mathematics, Physics, Cybersecurity Benefits: Access to a shared workspace (in either Berkeley, California or London, UK), Connection to the broader AI safety research community, Funding for compute (~$15k/month) and other research expenses, Optional equity donation matching, Generous vacation and parental leave, Flexible working hours