About Anthropic:
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Anthropic Fellows Program overview:
The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.

Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.

What to expect:
- 4 months of full-time research
- Direct mentorship from Anthropic researchers

- Access to a shared workspace (in either Berkeley, California or London, UK)
- Connection to the broader AI safety and security research community
- Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)
- Funding for compute (~$15k/month) and other research expenses

Interview process:
Compensation:
The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows workstreams:
- AI Safety Fellows
- AI Security Fellows
- ML Systems & Performance Fellows
- Reinforcement Learning Fellows
- Economics & Societal Impacts Fellows

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Across the workstreams, you may be a good fit if you:
- Are motivated by making sure AI is safe and beneficial for society as a whole
- Ar

Anthropic Fellows Program Reinforcement Learning

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