Anthropic is a public benefit corporation focused on building safe and beneficial AI systems. The role is part of the Inference team, responsible for scaling and optimizing the systems that serve Claude to millions of users worldwide. It involves designing distributed systems, intelligent request routing, load balancing, autoscaling, deployment pipelines, and supporting new AI accelerators and model architectures.
Staff + Sr. Software Engineer, Scaling en Anthropic
Híbrido - New York City, NY; San Francisco, CA; Seattle, WA
Más vacantes en AnthropicSalary
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 and multiple cloud providers
- Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers
- 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
PythonRustKubernetesAWSGCPAzure
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