Staff + Senior Software Engineer, Inference Deployment at Anthropic

Hybrid - San Francisco, CA; New York City, NY; Seattle, WA

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Anthropic’s Inference team builds and maintains critical systems that serve Claude to millions of users worldwide. The role focuses on designing, building, and maintaining distributed systems, improving compute efficiency, and enabling researchers with high-performance inference infrastructure across multiple accelerator families and cloud platforms.

Salary

USD 320,000 - 485,000

Requirements

Skills

  • Significant software engineering experience, particularly with distributed systems
  • 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
  • Experience with high-performance, large-scale distributed systems
  • Experience implementing and deploying machine learning systems at scale
  • Experience with load balancing, request routing, or traffic management systems
  • Familiarity with LLM inference optimization, batching, and caching strategies
  • Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure)
  • Proficiency in Python or Rust

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

KubernetesAWSGCPAzurePythonRust

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