Anthropic Research Resident

Anthropic•San Francisco, CA

7d•$350,000 - $500,000•Hybrid

About The Position

Anthropic’s paid, fixed-term Residency is for people who have led ambitious work in technical fields and want to transition to full-time work focused on making AI systems safe and beneficial. Machine learning experience is not required. Residents work on empirical research questions with Anthropic research teams through a concrete, scoped project matched to their background and receive direct mentorship from Anthropic researchers. They also have access to Claude models and GPU compute and connect with the broader AI safety and security research community. Placements last six weeks, three months, or six months, depending on team fit and candidate preferences. Other durations between three and six months may be possible by exception. Anthropic prefers Residents to work from its San Francisco office, though remote participation is possible, especially for shorter placements; remote participants must be based in a country where Anthropic can hire. The residency is full-time for its duration. Compensation is $350,000–$500,000 per year, prorated for the placement, plus benefits. Visa sponsorship is available for placements of three months or longer. Research areas include AI safety and alignment, scalable oversight, adversarial robustness and AI control, model organisms, model internals and interpretability, safeguards research, AI welfare, AI security and frontier red-teaming, ML systems, and reinforcement learning. Residents may also be considered for the Anthropic Fellows Program.

Requirements

Be motivated to make AI safe and beneficial for society.
Be excited to transition into full-time empirical AI research.
Have led ambitious work in a technical field; examples include being a professor in a quantitative discipline, a technical founder, or a staff-level engineer.
Thrive in fast-paced, collaborative environments.
Be able to implement ideas quickly and communicate clearly.
Have a bachelor’s degree or an equivalent combination of education, training, and/or experience.
Have a field of study relevant to the role, demonstrated through coursework, training, or professional experience.

Nice To Haves

Experience authoring research papers in machine learning, NLP, or AI safety.
Experience with LLMs, reinforcement learning, Kubernetes clusters, or complex shared codebases.

Responsibilities

Conduct empirical research in collaboration with Anthropic research teams.
Work on a scoped research project matched to the Resident’s background.
Contribute to research in areas such as AI safety and alignment, scalable oversight, adversarial robustness and AI control, model organisms, interpretability, safeguards, AI welfare, frontier red-teaming, ML systems, or reinforcement learning.