Anthropic· Software Engineering - Infrastructure· London, UK
Sr. Software Engineer, Inference
Classified Tasks (15)
Automate 0%Augment 100%Human-Only 0%
Augment (15)
AI assists, human decides
Build and maintain critical inference systems that serve Claude to millions of users worldwide
technical
Serve models via large-scale, compute-agnostic inference deployments
technical
Implement intelligent request routing across the inference stack
technical
Orchestrate fleet-wide operations across diverse AI accelerators
operational
Maximize compute efficiency to support explosive customer growth
analytical
Provide high-performance inference infrastructure to enable research and model development
technical
Design and implement distributed systems across multiple accelerator families and cloud platforms
technical
Design intelligent routing algorithms that optimize request distribution across thousands of accelerators
analytical
Autoscale the compute fleet to dynamically match supply with demand across production, research, and experimental workloads
operational
Build production-grade deployment pipelines for releasing new models to millions of users
technical
Integrate new AI accelerator platforms to maintain hardware-agnostic operations
technical
Develop and contribute inference features such as structured sampling and prompt caching
technical
Support inference for new model architectures
technical
Analyze observability data and tune system performance based on real-world production workloads
analytical
Manage multi-region deployments and configure geographic routing for global customers
operational
Job description
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. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. 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 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 multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Strong candidates may also have experience with: High-performance, large-scale distributed systems Implementing and deploying machine learning systems at scale Load balancing, request routing, or traffic management systems LLM inference optimization, batching, and caching strategies Kubernetes and cloud infrastructure (AWS, GCP) Python or Rust You may be a good fit if you: Have significant software engineering experience, particularly with distributed systems Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Want 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 Representative projects across the org: Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators 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 Integrating new AI accelerator platforms to maintain our 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 Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £225,000 — £325,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combina