Anthropic Fellows Program, Reinforcement Learning
$25k - $50k • Remote • London, UK; Ontario, CAN; Remote-Friendly, United States; San Francisco, CA
Posted 16d ago
Job Location
London, UK; Ontario, CAN; Remote-Friendly, United States; San Francisco, CA
Tech Stack
Remote Work Policy
Fully remote
Categories
Applied AI Engineer
About the job
Anthropic is seeking talented individuals for its Fellows Program, focusing on AI research and engineering. This program provides funding and mentorship to promising technical talent, regardless of prior experience, to work on empirical projects aligned with Anthropic's research priorities. The goal is to produce public outputs, such as research papers, contributing to the development of reliable, interpretable, and steerable AI systems that are safe and beneficial for society. Fellows will engage in full-time research for four months, with opportunities for extension, and will be mentored by Anthropic researchers.
Responsibilities
- Conduct empirical research aligned with Anthropic's research priorities.
- Produce public outputs, such as paper submissions.
- Work on projects related to Reinforcement Learning, potentially including building model-based tools to understand AI training data and improve its quality.
Requirements
- Strong technical background in computer science, mathematics, or physics.
- Fluent in Python programming.
- Available to work full-time on the Fellows program.
- Motivated by making AI safe and beneficial for society.
- Excited to transition into empirical AI research and potentially pursue a full-time role at Anthropic.
- Ability to implement ideas quickly and communicate clearly.
- Thrive in fast-paced, collaborative environments.
Benefits
- 4 months of full-time research.
- Direct mentorship from Anthropic researchers.
- Access to a shared workspace (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.
- Funding for compute (~$15k/month).
- Funding for other research expenses.