The Anthropic Fellows Program, Reinforcement Learning, invites promising technical talent to undertake a 4‑month full‑time research cohort. Fellows receive mentorship, funding for compute and research expenses, and a weekly stipend (3,850 USD / 2,310 GBP / 4,300 CAD). The role focuses on building reinforcement learning environments, improving model safety, and producing public outputs such as research papers. Applicants should have a strong background in computer science, mathematics, physics, or related disciplines, be fluent in Python, and be eager to transition into empirical AI research with a focus on safety and societal impact.
Anthropic Fellows Program, Reinforcement Learning en Anthropic
Remoto - London, UK; Ontario, CAN; Remote-Friendly, United States; San Francisco, CA
Más vacantes en AnthropicSalary
GBP 3,850 - 2,310
Requirements
Skills
- Strong technical background in computer science, mathematics, or physics
- Fluent in Python programming
- Available to work full-time
- Motivated by ensuring AI is safe and beneficial for society
- Excited to transition into empirical AI research and pursue a full-time role at Anthropic
- Thrive in fast‑paced, collaborative environments
- Can implement ideas quickly and communicate clearly
- Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
- Experience in areas of research or engineering related to their workstream
- Strong software engineering skills with experience building complex ML systems
- Balance research exploration with engineering rigor and operational reliability
- Comfortable working with large‑scale distributed systems
Responsibilities
- Conduct research on reinforcement learning projects aligned with Anthropic’s research priorities
- Build RL environments to improve Claude models on safety‑related tasks
- Implement solutions in RL algorithms and research areas such as generalization and data quality
- Produce public outputs such as papers
- Participate in weekly research discussions and mentorship sessions
- Operate within a shared workspace (Berkeley, CA or London, UK)
Technologies
Python
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