Software Engineer - Kubernetes / Accelerator Infrastructure

Anthropic
London

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

Anthropic is seeking talented and experienced Infrastructure Engineers to join our Core Infrastructure team and support the development, scaling, and maintenance of our cutting-edge AI systems. By joining our Core Infrastructure team, you will have the opportunity to work on groundbreaking AI technologies and contribute to the development of frontier models, supporting Anthropic's mission to create safe and reliable AI systems that benefit humanity.
The Core Infrastructure team is responsible for supporting some of the largest, most sophisticated clusters in the industry used to train, research, and ultimately serve AI models. Your work will be crucial in ensuring Anthropic can continue reliably and safely training frontier models. You will be responsible for building systems and running large Kubernetes clusters using GPU/TPU/Trainium accelerators.

Responsibilities

  • Pushing the frontier of Kubernetes scheduling for accelerators concentrating on efficient capacity use and customer experience

  • Lead the build-out of industry-leading compute clusters (thousands+ of machines), partnering closely with cloud service providers

  • Scheduler development and infrastructure hardening

  • Build and maintain large-scale Kubernetes clusters optimized for GPU/TPU/Trainium workloads

  • Design and implement systems that ensure reliability, scalability, and performance for frontier model training

  • Consult with research teams to deeply understand infrastructure and compute needs, identifying solutions to support frontier research

  • Set technical strategy and oversee development of high-scale, reliable infrastructure systems

You may be a good fit if you

  • Have experience leading large-scale, complex projects or teams as an engineer or tech lead

  • Are experienced with distributed systems at scale, infrastructure reliability, scalability, security, and continuous improvement

  • Have deep experience with Kubernetes and container orchestration at scale

  • Have strong proficiency in at least one programming language (e.g., Python, Rust, Go)

  • Have strong problem-solving skills and the ability to work independently

  • Have a passion for supporting internal partners like research teams to understand their needs

  • Have excellent communication skills to build consensus with stakeholders, both internally and externally

  • Possess deep knowledge of modern cloud infrastructure, including Infrastructure as Code, AWS, and GCP

Strong candidates may have:

  • Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL

  • Low-level systems experience, for example Linux kernel tuning and eBPF

  • Experience building and operating clusters at the scale of thousands+ of nodes

  • Technical expertise in quickly understanding systems design tradeoffs

The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.

Annual Salary:

£240,000—£325,000 GBP

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 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. 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

Posted 2025-11-08

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