Senior Software Engineer, Infrastructure

Posted 24 Days Ago
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London, Greater London, England
In-Office
240K-325K Annually
Senior level
Artificial Intelligence • Natural Language Processing • Generative AI
The Role
Lead the development and maintenance of large-scale AI infrastructure systems, ensuring reliability and scalability while mentoring team members and collaborating with stakeholders.
Summary Generated by Built In
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 team and support the development, scaling, and maintenance of our cutting-edge AI systems. By joining our 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.
 
Anthropic's Infrastructure organization is the engine that powers our mission to develop AI systems that are safe, beneficial, and understandable. Every breakthrough in AI safety research and every interaction users have with Claude depends on the systems we build and operate: massive clusters for training, production infrastructure serving millions of users reliably, and developer platforms that help engineers move fast without breaking things. And even with that, this isn't typical infrastructure work. We're building at the frontier of what's possible, solving novel scaling challenges that few organizations face with a high degree of security, all in service of ensuring transformative AI benefits humanity. If you're energized by your technical work directly enabling some of the most important research happening today, Infrastructure at Anthropic is the best place to make a real difference.
 
We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the infrastructure teams where they'll have the greatest impact and growth potential.
Responsibilities:
  • Lead build out of industry-leading AI clusters (thousands to hundreds of thousands of machines), partnering closely with cloud service providers on cluster build out and required features
  • Consult with different stakeholders to deeply understand infrastructure, data and compute needs, identifying potential solutions to support frontier research and product development
  • Set technical strategy and oversee development of high scale, reliable infrastructure systems.
  • Mentor top technical talent
  • Design processes (e.g. postmortem review, incident response, on-call rotations) that help the team operate effectively and never fail the same way twice
You may be a good fit if you:
  • Have 6+ years of relevant industry experience, 1+ year leading large scale, complex projects or teams as an engineer or tech lead
  • Are obsessed with distributed systems at scale, infrastructure reliability, scalability, security, and continuous improvement
  • Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)
  • Strong problem-solving skills and ability to work independently
  • Have a passion for supporting internal partners like research 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 Kubernetes, Infrastructure as Code, AWS, and GCP
Strong candidates may have:
  • Security and privacy best practice expertise
  • 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 
  • Technical expertise: Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

The annual compensation range for this role is listed below. 

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

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.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—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. 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

Top Skills

AWS
GCP
Go
Gpus
Infrastructure As Code
Java
Kubernetes
Linux
Python
Rust
Tpus
Trainium
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The Company
HQ: San Francisco, California
57 Employees

What We Do

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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