Staff Software Engineer, Inference

Staff Software Engineer, Inference

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
J

At a Glance

  • Tasks: Build and maintain AI systems that serve millions of users worldwide.
  • Company: Join Anthropic, a mission-driven tech company focused on safe and beneficial AI.
  • Benefits: Competitive pay, flexible hours, generous leave, and equity donation matching.
  • Other info: Diverse team culture that values collaboration and societal impact.
  • Why this job: Make a real impact in AI research while working with cutting-edge technology.
  • Qualifications: Experience in software engineering, particularly with distributed systems and performance optimisation.

The predicted salary is between 60000 - 80000 £ per year.

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

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.

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.

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.

Staff Software Engineer, Inference employer: job-boards.greenhouse.io- JobBoard

At Anthropic, we pride ourselves on being an exceptional employer dedicated to fostering a collaborative and innovative work culture. Our commitment to employee growth is reflected in our emphasis on impactful AI research and the opportunity to work with cutting-edge technology in a supportive environment. With competitive compensation, generous benefits, and a focus on work-life balance, we empower our team members to thrive both personally and professionally while contributing to the advancement of safe and beneficial AI systems.

J

Contact Details:

job-boards.greenhouse.io- JobBoard Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Software Engineer, Inference

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Contribute to Open Source Projects

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We think you need these skills to ace Staff Software Engineer, Inference

Performance Optimization
Distributed Systems
Large-Scale Service Orchestration
Intelligent Request Routing
LLM Inference Optimization
Batching Strategies
Multi-Accelerator Deployments

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at job-boards.greenhouse.io- JobBoard.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at job-boards.greenhouse.io- JobBoard and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at job-boards.greenhouse.io- JobBoard

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If job-boards.greenhouse.io- JobBoard uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.