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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:
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
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)
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.
Compensation
The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation. $300,000 - $485,000 USD
Logistics
Education requirements:
We require at least a Bachelor’s degree in a related field or equivalent experience.
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. Some roles may require more time in offices.
Visa sponsorship:
We do sponsor visas. If we make you an offer, we will make reasonable efforts to obtain a visa, with support from an immigration lawyer.
How we’re different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on a few large-scale research efforts with a focus on impact and steerable, trustworthy AI. We value collaboration, communication, and empirical progress in AI research.
#J-18808-Ljbffr
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:
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
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)
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.
Compensation
The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation. $300,000 - $485,000 USD
Logistics
Education requirements:
We require at least a Bachelor’s degree in a related field or equivalent experience.
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. Some roles may require more time in offices.
Visa sponsorship:
We do sponsor visas. If we make you an offer, we will make reasonable efforts to obtain a visa, with support from an immigration lawyer.
How we’re different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on a few large-scale research efforts with a focus on impact and steerable, trustworthy AI. We value collaboration, communication, and empirical progress in AI research.
#J-18808-Ljbffr