5 months ago
Responsibilities
- Conduct a full-time empirical research or engineering project aligned with Anthropic’s research priorities
- Build CPU simulators for accelerator workloads
- Add backends for different accelerators to open-source projects
- Build on-demand infrastructure for infrastructure-heavy research projects
- Develop complex synthetic data or environment pipelines
- Analyze and debug model training processes
- Collaborate with Anthropic researchers and engineering and research disciplines
- Produce a public output such as a paper submission
Requirements
- Strong technical background in computer science, mathematics, physics, or a related discipline
- Fluency in Python programming
- Availability to work full-time for the four-month program
- Strong software engineering skills and experience building complex ML systems are particularly valuable
- Experience with large-scale distributed systems and high-performance computing is particularly valuable
- Experience training, fine-tuning, or evaluating large language models is particularly valuable
- Ability to analyze and debug model training processes
- Work authorization in the US, UK, or Canada and the ability to be located in one of those countries during the program
- Relevant research or engineering experience is helpful but not required
Benefits
- Four-month full-time program with possible extension
- Weekly stipend plus country-specific benefits
- Direct mentorship from Anthropic researchers
- Access to shared workspaces in Berkeley or London
- Remote work available in the US, UK, or Canada
- Funding for compute and other research expenses
- Flexible workspace and collaboration with the broader AI safety and security research community
- Work authorization is required in the US, UK, or Canada; visa sponsorship is unavailable
- Next cohort starts July 20, 2026, with applications due April 26, 2026
Tech Stack
Categories
About Anthropic
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.