Staff + Senior Software Engineer, Inference Deployment

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI syst...

Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routi...

The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across...

Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems.
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

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
Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments
Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
Building production-grade deployment pipelines for releasing new models to millions of users reliably
Contributing to new inference features
Supporting inference for new model architectures
Analyzing observability data to tune performance based on real-world production workloads
Managing multi-region deployments and geographic routing for global customers