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Staff Software Engineer Inference

Applied Intuition Inc.

Greater London

Hybrid

GBP 80,000 - GBP 100,000

Full time

Today
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Job summary

A leading AI technology company in Greater London is seeking a Staff Software Engineer to enhance inference systems for AI models serving millions. Candidates should have strong experience in performance optimization and distributed systems. The role includes optimizing request routing and managing multi-accelerator deployments. The firm offers competitive benefits, a flexible work environment, and values diverse perspectives. Applicants are encouraged to apply even if they do not meet every requirement.

Benefits

Competitive compensation
Flexible working hours
Generous vacation and parental leave

Qualifications

  • Significant software engineering experience, particularly with distributed systems.
  • Results-oriented with a bias towards flexibility and impact.
  • Ability to work beyond defined job descriptions.

Responsibilities

  • Identifying infrastructure blockers to optimize service delivery.
  • Working across distributed systems to enhance inference capabilities.
  • Contributing to intelligent routing algorithms and autoscaling resources.

Skills

Performance optimization
Distributed systems
Large-scale service orchestration
Intelligent request routing
Kubernetes
Python
Rust

Education

Bachelor’s degree in a related field
Job description
About the role

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.

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. We will make every reasonable effort to get you a visa if we make you an offer, 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. We think AI systems like the ones we’re building have enormous social and ethical implications, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters contact from @anthropic.com email addresses. Legitimate recruiters will never ask for money, fees, or banking information before your first day. If you’re ever 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 just a few large-scale research efforts. 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. 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

Interested in building your career at Anthropic? Get future opportunities sent straight to your email.

We invite you to review our AI partnership guidelines for candidates and confirm your understanding by selecting “Yes.”

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