Staff Software Engineer, Inference na Anthropic

Híbrido - London, UK

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Anthropic’s Inference team builds and maintains the critical systems that serve Claude to millions of users worldwide, focusing on distributed systems, request routing, load balancing, autoscaling, and deployment pipelines across diverse AI accelerators and cloud platforms.

Salary

GBP 325,000 - 390,000

Requirements

Skills

  • Proficiency in Python or Rust
  • Software engineering experience building and operating distributed systems in production
  • Working knowledge of containerized infrastructure (e.g., Kubernetes) and at least one major cloud platform (AWS, GCP, or Azure)
  • Results-oriented, with a bias towards flexibility and impact
  • Willingness to pick up slack, even if it goes outside your job description
  • Desire to learn more about machine learning systems and infrastructure
  • Thrive in environments where technical excellence directly drives both business results and research breakthroughs
  • Care about the societal impacts of your work
  • Significant experience with high-performance, large-scale distributed systems
  • Experience implementing and deploying machine learning systems at scale
  • Experience building load balancing, request routing, or traffic management systems
  • Familiarity with LLM inference optimization, batching, and caching strategies
  • Deep experience operating Kubernetes and cloud infrastructure at scale
  • Experience with AI accelerator platforms (GPUs, TPUs, or emerging hardware)

Responsibilities

  • Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide
  • Develop resilient, flexible systems that adapt in real time to real-world events
  • Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators
  • Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads
  • Build and operate production-grade deployment pipelines for releasing new models to users
  • Provide high-performance inference infrastructure that enables researchers to develop next-generation models
  • Integrate new AI accelerator platforms and support inference for new model architectures

Technologies

PythonRustKubernetesAWSGCPAzureLLM inference optimizationBatchingCachingAI accelerators (GPUs, TPUs, emerging hardware)

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