Senior Staff Software Development Engineer

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.
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, 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.
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
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
Desire to learn more about machine learning systems and infrastructure
Thrive in environments where technical excellence directly drives both business results and research breakthroughs
Experience with high-performance, large-scale distributed systems
Experience implementing and deploying machine learning systems at scale
Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure)
Proficiency in Python or Rust
Representative projects
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
Analyzing observability data to tune performance based on real-world production workloads
Managing multi-region deployments and geographic routing for global customers

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: 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.
We think AI systems like the ones we're building have enormous social and ethical implications. We believe that the highest-impact AI research will be big science. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.