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Staff + Sr. Software Engineer, Scaling

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Staff + Sr. Software Engineer, Scaling in USA

  • Anthropic
  • Full time
  • Email
  • Seattle, WA

Responsibilities

  • Design, build, and maintain distributed systems serving Claude to millions of users worldwide.
  • Develop intelligent routing, load balancing, traffic management, autoscaling, and orchestration systems across thousands of accelerators and multiple cloud providers.
  • Build and operate production-grade deployment pipelines for releasing new models reliably.
  • Provide high-performance inference infrastructure for machine-learning research and support new model architectures and AI accelerator platforms.
  • Analyze observability data, tune production performance, and manage multi-region deployments and geographic routing.

Requirements

  • Significant software engineering experience, particularly with distributed systems.
  • Experience with high-performance, large-scale distributed systems is preferred.
  • Experience implementing and deploying machine-learning systems at scale is preferred.
  • Experience with load balancing, request routing, or traffic management systems is preferred.
  • Familiarity with LLM inference optimization, batching, and caching strategies is preferred.
  • Experience with Kubernetes and cloud infrastructure such as AWS, GCP, and Azure is preferred.
  • Proficiency in Python or Rust is preferred.
  • A results-oriented, flexible approach and willingness to work beyond narrowly defined responsibilities.
  • Interest in machine-learning systems and infrastructure and awareness of the societal impacts of the work.

Benefits

  • Hybrid work policy requiring staff to work from an Anthropic office at least 25% of the time.
  • Visa sponsorship is available, subject to role and candidate eligibility.
  • Competitive benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.

Salary: $320k - $485k/yr

Anthropic

Anthropic builds AI systems that are reliable, interpretable, and steerable, with a commitment to ensuring their safety and benefit to users and society. Our work is driven by a dedicated team of researchers, engineers, and policy experts focused on the development of beneficial AI solutions.

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