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Research Engineer

anthropic • United States
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AI Summary

Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment. Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities. Have 6+ years of highly-relevant experience in infrastructure engineering with demonstrated expertise in large-scale distributed systems.

Key Highlights
Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment.
Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities.
Have 6+ years of highly-relevant experience in infrastructure engineering with demonstrated expertise in large-scale distributed systems.

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Key Responsibilities
Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments
Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities
Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI.
Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows
Collaborate to translate experimental requirements into production-ready infrastructure
Develop large scale data pipelines to handle advanced language model training requirements
Optimize large scale training and inference pipelines for stable and efficient reinforcement learning
Technical Skills Required
Distributed Systems Containerization Data Pipelines

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Benefits & Perks
Competitive compensation
Generous vacation
Parental leave
Flexible working hours

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Nice to Have
Experience with language model training infrastructure and distributed ML frameworks (PyTorch, JAX, etc.)
Background in building infrastructure for AI research labs or large-scale ML organizations
Knowledge of GPU/TPU architectures and language model inference optimization
Experience with cloud platforms (AWS, GCP) at enterprise scale
Familiarity with VM and container orchestration.
Experience with workflow orchestration tools and experiment management systems
History working with large scale reinforcement learning
Comfort with large scale data pipelines (Beam, Spark, Dask, …)

Job Description

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for our society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About The Team

Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier.

About The Role

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Job Overview
Posted Nov 10, 2026
Employment Full-time
Experience Mid-Senior level
Location United States
Category Devops
Company anthropic
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