Research Engineer, Machine Learning (Reinforcement Learning)

Anthropic is a public benefit corporation dedicated to creating reliable and beneficial AI systems. The Research Engineer within Reinforcement Learning will collaborate with researchers and engineers to advance the capabilities and safety of large language models through research and engineering responsibilities.

Responsibilities:

• Architect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters
• Help scale our systems to handle increasingly complex research workflows
• Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents which push the state of the art for the next generation of models
• Drive performance improvements across our stack through profiling, optimization, and benchmarking
• Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation workflows
• Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research