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Anthropic

Anthropic Fellows Program, Reinforcement Learning

OtherPart-TimeMid-Level
Location
Worldwide
Job Type
Part-Time
Experience
Mid-Level
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Job Description

ABOUT THE ROLE Anthropic is a company dedicated to creating reliable, interpretable, and steerable AI systems. Our mission is to ensure that AI is safe and beneficial for society as a whole. We are seeking talented researchers and engineers to join our Anthropic Fellows Program, a 4-month full-time research opportunity that fosters AI research and engineering talent. WHAT YOU'LL DO As an Anthropic Fellow, you will work on an empirical project aligned with our research priorities, using external infrastructure such as open-source models and public APIs. Your goal will be to produce a public output, such as a paper submission. You will have the opportunity to collaborate with our team of researchers and engineers, and you will be directly mentored by Anthropic researchers. WHAT YOU'LL NEED To be a strong candidate for this role, you should have a strong technical background in computer science, mathematics, or physics. You should be motivated by making sure AI is safe and beneficial for society as a whole, and you should be excited to transition into empirical AI research. You should also be fluent in Python programming and available to work full-time on the Fellows program. WHY REMOTE As an Anthropic Fellow, you will have the opportunity to work remotely from either Berkeley, California, or London, UK. You will have access to a shared workspace and will be connected to the broader AI safety and security research community. BENEFITS As an Anthropic Fellow, you will receive a weekly stipend of $3,850 USD / £2,310 GBP / $4,300 CAD, plus benefits that vary by country. You will also receive funding for compute and other research expenses. We encourage you to apply even if you do not believe you meet every single qualification. We strive to include a range of diverse perspectives on our team and believe that representation is essential in the development of AI systems.