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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.
  • Develop intelligent request routing, load balancing, traffic management, autoscaling, and fleet orchestration across accelerators and cloud providers.
  • Build and operate production-grade deployment pipelines for releasing new models reliably.
  • Optimize inference performance, compute efficiency, and infrastructure costs across production, research, and experimental workloads.
  • Integrate new AI accelerator platforms and support inference for new model architectures.
  • Analyze observability data, tune production performance, and manage multi-region and geographic routing deployments.

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, or Azure is preferred.
  • Proficiency in Python or Rust is preferred.
  • Bachelor’s degree or an equivalent combination of education, training, and/or experience in a relevant field.

Benefits

  • Hybrid policy requiring staff to work from an office at least 25% of the time.
  • Competitive benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.
  • Visa sponsorship is offered with reasonable efforts made after an offer, although sponsorship cannot be successfully provided for every role or candidate.

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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