Staff Software Engineer, Inference

Mat Vin; Greater London; Hybrid; GBP 325,000 - 390,000; Full time

Benefits offered by this job

Competitive compensation

Equity donation matching

Generous vacation and parental leave

Flexible working hours

Office space

Job summary

Anthropic in London, UK, is hiring a Staff Software Engineer for Inference to build scalable, high-performance distributed systems. You will work across the stack to serve Claude to millions of users, manage real-time workloads, and optimize inference infrastructure.

The role emphasizes Python or Rust proficiency, containerized environments (Kubernetes), and cloud platforms (AWS, GCP, Azure) within a hybrid office setting. Visa sponsorship available for capable candidates.

Qualifications

• Experience designing and building large-scale distributed systems.
• Proficiency in modern programming languages and systems software.
• Experience operating in production-grade distributed inference infrastructure.

Responsibilities

• Design, build, and maintain distributed systems serving Claude to millions of users.
• Develop resilient, real-time adaptive systems for real-world events.
• Develop intelligent routing, load balancing, and traffic management across accelerators.
• Maximize compute efficiency via autoscaling and orchestration of workloads.
• Build and operate production-grade deployment pipelines for models.
• Provide high-performance inference infrastructure for research and development.
• Integrate new AI accelerator platforms and support new model architectures.
• Demonstrate proficiency in Python or Rust.

Skills

Python

Rust

Distributed systems

Kubernetes

AWS

GCP

Azure

Software engineering

Education

Bachelor0s degree

Tools

Python

Job description

Staff Software Engineer, Inference

London, UK

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.

Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

Key responsibilities

• Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide
• Develop resilient, flexible systems that adapt in real time to real-world events
• Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators
• Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads
• Build and operate production-grade deployment pipelines for releasing new models to users
• Provide high-performance inference infrastructure that enables researchers to develop next-generation models
• Integrate new AI accelerator platforms and support inference for new model architectures
• Proficiency in Python or Rust
• Software engineering experience building and operating distributed systems in production
• Working knowledge of containerized infrastructure (e.g., Kubernetes) and at least one major cloud platform (AWS, GCP, or Azure)
• Results-oriented, with a bias towards flexibility and impact
• Willingness to pick up slack, even if it goes outside your job description
• Desire 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

Preferred qualifications

• Significant experience with high-performance, large-scale distributed systems
• Experience implementing and deploying machine learning systems at scale
• Experience building load balancing, request routing, or traffic management systems
• Familiarity with LLM inference optimization, batching, and caching strategies
• Deep experience operating Kubernetes and cloud infrastructure at scale
• Experience with AI accelerator platforms (GPUs, TPUs, or emerging hardware)

Representative projects

• Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments
• 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 reliably
• Contributing to new inference features
• 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

Deadline to apply: None. Applications will be reviewed on a rolling basis.

The annual compensation range for this role is listed below.

Annual Salary:

£325,000 - £390,000 GBP

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

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

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.

• competitive compensation and benefits
• optional equity donation matching
• generous vacation and parental leave
• flexible working hours
• a lovely office space in which to collaborate with colleagues

Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.