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.
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
- Enjoy pair programming (we love to pair!)
- 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
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, Azure)
- Python or Rust
Representative projects:
- 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
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.