Anthropic Fellows Program, ML Systems & Performance
Core
Empirical AI research and engineering project focused on ML systems, performance, and infrastructure, producing public outputs like papers.
Role type
Research Fellow (ML Systems & Performance)
Builds
CPU simulators for accelerator workloads, backends for accelerators, on-demand infrastructure, complex synthetic data pipelines
Domain
Artificial Intelligence, Machine Learning Systems, High-Performance Computing
Deliverable
research
Required skills
Python programming, software engineering, building complex ML systems, analyzing and debugging model training processes, working with large-scale distributed systems, training/fine-tuning/evaluating LLMs
Preferred skills
experience in cybersecurity, economics, or social sciences, experience in trading or high-frequency systems
Technologies
Python, open-source models, public APIs, accelerators
Responsibilities
Conduct empirical research aligned with AI safety priorities, implement engineering solutions for ML infrastructure, collaborate with mentors and researchers, produce public research outputs
Seniority
Early career / Fellow (no prior experience required, but strong technical background needed)
