Staff Software Engineer (Inference)

Anthropic; Dublin; On-site; EUR 120,000 - 180,000; Full time

Benefits offered by this job

Competitive compensation

Flexible working hours

Generous vacation and parental leave

Office space for collaboration

Job summary

A technology company focused on AI in Dublin is seeking a Staff Software Engineer for the Inference team. You will optimize infrastructure to serve AI models to millions of users. Candidates should have experience in performance optimization and distributed systems. This role offers opportunities to contribute to impactful AI research and requires at least a Bachelor's degree. Hybrid work is expected part-time in the office.

Qualifications

• Significant software engineering experience, particularly with distributed systems.
• Results-oriented, with a bias towards flexibility and impact.
• Willing to pick up slack, even if it goes outside your job description.
• Desire to learn more about machine learning systems and infrastructure.
• Able to thrive in environments where technical excellence drives business results.

Responsibilities

• Identify and address key infrastructure blockers.
• Serve Claude to millions of users.
• Enable breakthrough AI research.
• Design intelligent routing algorithms.
• Autoscale compute fleet to match supply with demand.

Skills

Performance optimization

Distributed systems

Large-scale service orchestration

Intelligent request routing

Load balancing

Request routing

Traffic management systems

Kubernetes

Cloud infrastructure (AWS, GCP)

Python

Rust

Education

Bachelor's degree in a related field

Tools

Kubernetes

AWS

GCP

Job description

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.

As a Staff Software Engineer on our Inference team, you will work to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large‑scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi‑accelerator deployments is highly encouraged but not strictly necessary.

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

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

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

Representative projects across the org:

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.

The expectedbase compensation for this position is below. Our total compensation package for full‑time employees includes equity, benefits, and may include incentive compensation.

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. 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.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

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 just a few large‑scale research efforts. 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. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest‑impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT‑3, Circuit‑Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

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 aboutour policy for using AI in our application process