Software Engineer, Core Infrastructure

Anthropic; London; Hybrid; GBP 70,000 - 90,000; Full time

Job summary

A leading AI company in London is seeking an experienced Infrastructure Engineer to join their Core Infrastructure team. The role involves building and maintaining large-scale Kubernetes clusters to support cutting-edge AI technologies. Candidates should have extensive experience leading projects and working with cloud infrastructure. This position offers competitive compensation and a hybrid work policy.

Benefits

Competitive compensation

Generous vacation and parental leave

Flexible working hours

Qualifications

• Experience with large-scale, complex projects as an engineer or tech lead.
• Proficient with infrastructure reliability, scalability, and security.
• Deep knowledge of modern cloud infrastructure and Infrastructure as Code.

Responsibilities

• Lead the build-out of compute clusters partnering with cloud providers.
• Maintain large-scale Kubernetes clusters optimized for workloads.
• Design systems for reliability and performance in model training.

Skills

Leadership in large-scale projects

Distributed systems expertise

Kubernetes proficiency

Programming skills (Python, Rust, Go)

Excellent communication

Education

Bachelor's degree in a related field

Tools

Kubernetes

AWS

GCP

Job description

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

• Lead the build-out of industry-leading compute clusters (thousands+ of machines), partnering closely with cloud service providers
• 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 and keeping track of rapidly evolving software systems

The expected salary range for this position is:

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. 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. 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. 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.

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