Staff Software Engineer, Inference

Key Responsibilities

• Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide
• 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
• Use observability data to tune and improve performance based on real-world production workloads

Representative Projects

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling 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
• Integrating new AI accelerator platforms to maintain hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• 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

Minimum Qualifications

• 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
• Enjoy pair programming
• 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

Preferred Qualifications

• 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

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.