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Anthropic Research Resident

$350k - $500k • Remote • San Francisco, CA | New York City, NY

Posted 23h ago

Job Location

San Francisco, CA | New York City, NY

Tech Stack

Anthropic Kubernetes LLM NLP Reinforcement Learning RLHF ML systems Red-teaming Interpretability AI safety AI Alignment AI security model internals Scalable Oversight Adversarial Robustness Safeguards Research AI Welfare

Remote Work Policy

Fully remote

About the job

Anthropic is seeking individuals for a paid, fixed-term research residency program, lasting between six weeks and six months. This program is designed for experienced professionals, such as professors in quantitative disciplines, technical founders, or staff-level engineers, who are looking to transition into full-time work focused on ensuring AI systems are safe and beneficial for humanity. While a background in machine learning is not strictly required, candidates should be motivated by AI safety and excited about empirical AI research. The residency offers a scoped project with direct mentorship from Anthropic researchers, access to Claude models and GPU compute, and connections to the AI safety and security research community.

Responsibilities

Conduct empirical research on AI safety and alignment, including scalable oversight, adversarial robustness, model organisms of misalignment, model internals and interpretability, safeguards research, and AI welfare.
Engage in AI security and frontier red-teaming by stress-testing frontier models for capabilities in areas like cybersecurity, robotics, or cryptography.
Contribute to ML systems and reinforcement learning by improving frontier model training and building research infrastructure, including model architecture, optimizers, training data, accelerator simulators, hardware backends, and RL environment pipelines.
Collaborate with Anthropic researchers on defined projects.
Implement ideas quickly and communicate clearly.

Requirements

Motivated by ensuring AI is safe and beneficial for society.
Excited to transition into full-time empirical AI research.
Have led ambitious work in a variety of technical fields (e.g., professor in a quantitative discipline, technical founder, staff-level engineer).
Thrive in fast-paced, collaborative environments.
Ability to implement ideas quickly and communicate clearly.

Benefits

Paid residency
Access to Claude models
Access to GPU compute

About Anthropic

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