Staff Software Engineer, Inference

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

Job summary

Anthropic is seeking engineers for the Inference team to design and maintain the systems that serve Claude to millions of users. You will build scalable, resilient infrastructure, implement intelligent routing and traffic management, and maximize compute efficiency across diverse accelerators in multi-cloud environments.

Join a team focused on reliable AI and high-performance delivery, with opportunities to work across production, research, and deployment pipelines and to influence real-world AI

Qualifications

• 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 flexibility and impact.
• Willingness to pick up slack beyond job description.
• Desire to learn more about ML systems and infrastructure.

Responsibilities

• Design, build, and maintain distributed systems serving Claude to millions of users.
• Develop resilient, flexible systems adapting in real time to events.
• Develop intelligent request routing, load balancing, and traffic management across accelerators.
• Maximize compute efficiency via autoscaling and orchestration of workloads.
• Build and operate production pipelines for releasing new models.

Skills

Python or Rust

Distributed systems

Kubernetes

Cloud platforms

Problem-solving

Learning mindset

Education

Bachelor's degree

Tools

Kubernetes

AWS

GCP

Azure

Job description

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 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.

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

Minimum Qualifications

• 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 reliablyContributing 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

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.

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 about our policy for using AI in our application process.

Guidance on Candidates' AI Usage:

Learn about our policy for using AI in our application process.