Research Engineer, Discovery

About this role

Build infrastructure across the model stack to support an AI scientist capable of advancing scientific research. The role focuses on removing infrastructure bottlenecks and enabling training, evaluation, and safe execution of long-horizon AI tasks.

About the company

Anthropic builds reliable and interpretable AI systems, including the Claude family of models, for businesses and developers. The company focuses on AI safety research and practical AI assistants for enterprise and consumer use.

The team

Discovery team, focused on building an AI scientist.

Stack

What you'll do

• Design distributed infrastructure for AI scientist training, evaluation, and deployment
• Identify and resolve infrastructure bottlenecks
• Build evaluation frameworks to measure progress toward scientific AGI
• Develop VM, sandbox, and container architectures for safe execution of long-horizon tasks
• Build large-scale data pipelines for language model training
• Optimize training and inference pipelines for stable, efficient reinforcement learning

What we're looking for

• 6+ years of relevant infrastructure engineering experience, including large-scale distributed systems
• Strong knowledge of performance optimization and system architectures for high-throughput ML workloads
• Experience with containerization and orchestration at scale
• Track record building large-scale data pipelines and distributed storage systems
• Ability to diagnose production infrastructure challenges and work across the ML stack
• Strong communication and collaboration skills

Nice to have

• Language model training infrastructure and distributed ML frameworks
• Experience building infrastructure for AI research labs or large-scale ML organizations
• GPU/TPU architecture and language model inference optimization
• Enterprise-scale AWS or GCP experience
• VM and container orchestration, workflow orchestration, or experiment management
• Large-scale reinforcement learning experience