Senior AI Inference Engineer – Distributed Systems

Neura Market; Dublin; Hybrid; EUR 235,000 - 295,000; Full time

Job summary

Anthropic in Ireland is seeking an experienced software engineer for its Inference team to build and maintain high-scale AI inference systems powering Claude for millions of users. You will work across the stack from routing to fleet orchestration across multiple cloud platforms and accelerators.

The role emphasizes compute efficiency, enabling breakthrough research, and collaboration with researchers and engineers. Hybrid office policy applies; visa sponsorship available for suitable candidates.

Qualifications

• Significant software engineering experience, particularly with distributed systems.
• Experience deploying ML systems at scale and operating inference workloads.
• Familiarity with cloud infrastructure and container orchestration.

Responsibilities

• Design intelligent routing algorithms to optimize request distribution across accelerators.
• Develop autoscaling for compute fleets across production and research workloads.
• Build production-grade deployment pipelines for releasing new models to users.
• Integrate new AI accelerator platforms to maintain hardware-agnostic advantage.
• Contribute to inference features such as structured sampling and prompt caching.

Skills

Distributed systems

Large-scale deployment

Load balancing

HTTP routing

Python

Rust

Cloud infrastructure

Collaboration

Education

Bachelor’s degree in a field relevant to the role

Tools

Kubernetes

AWS

GCP

Job description

Anthropic in Ireland is seeking an experienced software engineer for its Inference team to build and maintain high-scale AI inference systems powering Claude for millions of users. You will work across the stack from routing to fleet orchestration across multiple cloud platforms and accelerators.

The role emphasizes compute efficiency, enabling breakthrough research, and collaboration with researchers and engineers. Hybrid office policy applies; visa sponsorship available for suitable candidates.