Staff + Senior Software Engineer, Inference Deployment

Details

About Anthropic

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.

About the role

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 routing to fleet-wide orchestration across diverse AI accelerators.

The team has a dual mandate:

• Maximizing compute efficiency to reliably serve our explosive customer growth
• Enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models

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.

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
• 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

Requirements

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
• 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

Representative projects

• 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

Logistics

• 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, they aren't able to successfully sponsor visas for every role and every candidate. If they make you an offer, they will make every reasonable effort to get you a visa and retain an immigration lawyer to help with this.
• 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
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Apply

Deadline to apply: None. Applications will be reviewed on a rolling basis.

Compensation

Annual Salary: $320,000 - $485,000 USD