Anthropic Fellows Program, ML Systems & Reinforcement Learning
Machine Learning, Reinforcement Learning, Distributed Computing and research fellowship at Anthropic
About
Four-month, full-time research fellowship developing machine-learning infrastructure and reinforcement-learning methods. Projects can address training performance, distributed systems, synthetic-data and environment pipelines, or model generalization. Fellows receive researcher mentorship, a weekly stipend and benefits. Applications are reviewed on a rolling basis for the next cohort, expected in January 2027. San Francisco workspace access and remote participation from the United States, United Kingdom or Canada are available. A subsequent permanent role is not guaranteed.
Topics
- machine-learning infrastructure
- reinforcement-learning methods
- training performance
- distributed systems
- environment pipelines
- model generalization
- researcher mentorship
- San Francisco
- remote participation
Requirements
Fluent Python and availability for full-time participation. Strong technical foundations and relevant ML engineering, systems or reinforcement-learning experience are useful. Fellows must be located in, and independently hold full-time work authorization for, the United States, United Kingdom or Canada; the fellowship does not sponsor visas. Apply through the form on the official role page.
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Source: Anthropic