Anthropic Research Resident

Anthropic • San Francisco, NY

6d • Hybrid

About The Position

Anthropic’s paid, fixed-term Residency is a full-time empirical research program lasting six weeks to six months, with other placements between three and six months possible by exception. Residents join Anthropic research teams to work on a concrete, scoped project matched to their background, with direct mentorship from Anthropic researchers. The program is intended 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 may work on AI safety and alignment, AI security and frontier red-teaming, or machine-learning systems and reinforcement learning. Research topics include scalable oversight, adversarial robustness and AI control, model organisms, interpretability, safeguards, AI welfare, frontier-model stress testing, and infrastructure for training frontier models. Residents receive access to Claude models, GPU compute, and the broader AI safety and security research community.

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 company currently expects staff to work from one of its offices at least 25% of the time, although some roles may require more. Visa sponsorship is available for placements of three months or longer, and Anthropic will make reasonable efforts to sponsor visas for offers where possible.

The interview process includes an application, recruiter screen, technical assessment, research discussion, and reference check. Applications for this round close November 22, 2026, at 11:59 PM PT; offers are expected in January 2027. Annual compensation is $350,000–$500,000 USD, prorated for the residency duration, plus benefits.

Requirements

• Bachelor’s degree or an equivalent combination of education, training, and/or experience.
• A field relevant to the role, demonstrated through coursework, training, or professional experience.
• Experience leading ambitious work in a technical field; examples include being a professor in a quantitative discipline, a technical founder, or a staff-level engineer.
• Motivation to help ensure AI is safe and beneficial for society.
• Interest in transitioning to full-time empirical AI research.
• Ability to thrive in fast-paced, collaborative environments.
• Ability to implement ideas quickly and communicate clearly.
• Full-time availability for the duration of the residency.
• Minimum years of experience will correlate with the internal job level requirements; no specific number is stated.

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 on scoped questions in collaboration with Anthropic research teams.
• Work on research areas such as AI safety and alignment, AI security and frontier red-teaming, or machine-learning systems and reinforcement learning.
• Develop and evaluate methods for improving the safety, robustness, interpretability, oversight, or training of AI systems, depending on project and team fit.

Benefits

• Access to Claude models and GPU compute.
• Connection to the broader AI safety and security research community.
• Competitive compensation and benefits.
• Optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours.
• Office space for collaborating with colleagues.
• Visa sponsorship for placements of three months or longer, subject to the stated conditions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior