Staff Software Engineer, Inference

job-boards.greenhouse.io- JobBoard; Greater London; On-site; GBP 80,000 - 100,000; Full time

Benefits offered by this job

Competitive compensation

Generous vacation

Flexible working hours

Job summary

A leading AI research organization in the UK is seeking a Staff Software Engineer to join its Inference team. In this role, you will optimize systems that serve AI models to millions of users, focusing on infrastructure for breakthrough AI research. Candidates should have significant experience in software engineering, especially with distributed systems, and may possess familiarity with performance optimization and cloud infrastructure. This position offers competitive compensation and a collaborative working environment.

Qualifications

• Significant software engineering experience, particularly with distributed systems.
• Results-oriented, with a bias towards flexibility and impact.
• Eager to learn more about machine learning systems and infrastructure.

Responsibilities

• Work end to end on infrastructure to serve Claude to millions of users.
• Optimize performance for AI research.
• Implement intelligent routing algorithms for request distribution.

Skills

Performance optimization

Distributed systems

Large-scale service orchestration

Intelligent request routing

Python or 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 end 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.

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 sponsor visas. However, we aren’t able to sponsor every role or every candidate. If we make you an offer, we will make every reasonable effort to obtain a visa, and we may retain an immigration lawyer to assist with this.

We encourage you to apply even if you do not meet every single qualification. Not all strong candidates will meet every listed qualification. We urge you to apply if you’re interested, as a diverse team helps us address the societal and ethical implications of AI.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters contact candidates from @anthropic.com email addresses. Be cautious of emails from other domains. Legitimate recruiters will never ask for money, fees, or banking information before your first day. If you’re unsure about a communication, visit anthropic.com/careers directly for confirmed position openings.

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 a few large-scale research efforts and value impact—advancing our long-term goals of steerable, trustworthy AI. We emphasize collaboration, frequent research discussions, and strong communication skills.

The easiest way to understand our research directions is to read our recent work, including topics like 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. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a collaborative office environment.