Staff Software Engineer, Inference en Anthropic

Híbrido - Dublin, IE

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The Inference team at Anthropic is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. As a Staff Software Engineer on this team, you will work end‑to‑end to optimize compute efficiency and enable breakthrough research by developing high‑performance inference infrastructure across diverse AI accelerators.

Salary

EUR 295,000 - 355,000

Requirements

Skills

  • Bachelor’s degree or an equivalent combination of education, training, and/or experience
  • Significant software engineering experience, particularly with distributed systems
  • Familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing
  • Experience with LLM inference optimization, batching strategies, and multi-accelerator deployments (highly encouraged)
  • Knowledge of Kubernetes and cloud infrastructure (AWS, GCP)
  • Proficiency in Python or Rust

Responsibilities

  • Build and maintain critical inference systems that serve Claude to millions of users worldwide
  • Maximize compute efficiency to support explosive customer growth
  • Enable breakthrough research by providing high-performance inference infrastructure to scientists
  • Design intelligent routing algorithms to optimize request distribution across thousands of accelerators
  • Autoscale compute fleet to dynamically match supply with demand across production, research, and experimental workloads
  • Build production‑grade deployment pipelines for releasing new models to millions of users
  • Integrate new AI accelerator platforms to maintain hardware‑agnostic advantage
  • Support inference for new model architectures and analyze observability data to tune performance based on real‑world production workloads
  • Manage multi‑region deployments and geographic routing for global customers

Technologies

PythonRustKubernetesAWSGCPLLM inference optimizationBatching strategiesCaching strategies

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