Anthropic Fellows Program, ML Systems & Performance

The role

This is a time-bound fellowship within Anthropic's expanded Fellows Program focused on machine learning systems and performance optimization. Fellows conduct full-time empirical research projects under direct mentorship from senior researchers, with the goal of producing publishable work. The role targets early-career technical talent without prior experience requirements and offers funding, workspace access, and integration into the broader AI research community.

What you'd do

• Conduct four months of full-time empirical research on assigned ML systems project
• Work with external infrastructure including open-source models and public APIs
• Implement research ideas quickly while maintaining engineering rigor
• Analyze and debug model training processes
• Collaborate across research and engineering teams
• Produce public research output such as paper submissions
• Participate in project selection and mentor matching process

What they're looking for

• Fluent in Python programming
• Strong technical background in computer science, mathematics, or physics
• Available for full-time commitment during four-month program
• Work authorization in US, UK, or Canada
• Located in US, UK, or Canada during program
• Motivated by AI safety and beneficial AI development
• Ability to communicate clearly and work collaboratively

Nice to have

• Strong software engineering skills building complex ML systems
• Experience with large-scale distributed systems and high-performance computing
• Background in training, fine-tuning, or evaluating large language models
• Experience in areas related to ML systems research or engineering
• Background in trading or other HPC-intensive domains