Senior Software Engineer, Inference

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source

Seniority

Senior From the posting source

Schedule

Shift type

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Weekend work

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Company

Equity

Offered From the posting source

Application

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Assessment

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Deadline

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State eligibility is not yet verified.

About this role

Senior Software Engineer, Inference Dublin, IE 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

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