Location requirements
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.
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. 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.
The Systems engineering team enables Anthropic to rapidly research and deploy safe frontier models at scale by owning compute uptime and resilience. We build resilience into Anthropic's infrastructure and support rapid scaling of our clusters with frontier hardware through relentless automation. This allows Anthropic's research to remain on the frontier of what's possible and makes research breakthroughs safely and reliably deployable to customers.
We are seeking an experienced engineering leader to manage the part of our Systems team that looks after our Kubernetes control plane and custom schedulers. You'll lead initiatives 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.
Manage a team of engineers building and operating world-class infrastructure at scale
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 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
Hire and coach 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
Drive continuous improvement in system reliability, scalability, and security
Work closely with Research and Product Engineering teams to ensure infrastructure meets their evolving needs
Have 3+ years of experience managing technical teams of more than 6 people
Have strong leadership ability with experience managing and growing senior engineers
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, and major cloud providers (AWS, GCP)
Are passionate about infrastructure reliability, scalability, security, and continuous improvement
Have a track record of supporting internal partners and understanding their needs
Machine learning infrastructure including accelerators (GPUs, TPUs, Trainium) and supporting networking infrastructure like NCCL
Container orchestration platforms such as EKS and GKE
Working on teams that contribute to OSS Kubernetes and other CNCF tools
Infrastructure as Code tools like Terraform
Autoscaling technologies including Cluster Autoscaler and Karpenter
Low-level systems experience, for example Linux kernel tuning and eBPF
Security and privacy best practice expertise
Managing initiatives across multiple products and teams
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.
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.
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.
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
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