Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Go @ 7
Kubernetes @ 4
Linux @ 4
IaC @ 4
Terraform @ 7
Python @ 7
GCP @ 4
Distributed Systems @ 4
Machine Learning @ 4
AWS @ 4
Azure @ 4
Communication @ 4
Networking @ 3
Rust @ 7
GPU @ 4
AI @ 4
InfiniBand @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users.
Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major CSPs and our own datacenters, stand up and scale clusters from thousands to hundreds of thousands of hosts, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic’s frontier AI research.
Responsibilities
- Own the technical strategy and roadmap for node lifecycle management — ingestion, bring-up, health checking, and automated repair
- Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families
- Design and operate systems that detect, isolate, and remediate unhealthy hardware automatically, improving fleet MTBI and minimizing stranded capacity
- Define infrastructure architecture and ensure hard problems get solved either directly or by working through others
- Work closely with cloud providers and internal research, inference, and product teams to shape long-term compute, data, and infrastructure strategy
- Establish and evolve operational excellence practices (incident response, postmortem culture, on-call)
- Support growth of engineers through technical mentorship and coaching
Requirements
Minimum qualifications
- Deep expertise in distributed systems, reliability, and cloud platforms (examples: Kubernetes, IaC, AWS/GCP/Azure)
- Strong proficiency in at least one systems language (examples: Rust, Go, or Python); IaC proficiency with Terraform
- Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium)
- Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems
- Ability to build alignment across senior stakeholders and communicate effectively at all levels
Preferred qualifications
- 8+ years of software engineering experience, including time as a technical lead setting direction for a team
- Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency
- Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines
- Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons
- Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads
- Demonstrated ownership of production reliability for high-throughput, latency-sensitive systems
- Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.)
- Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems
Compensation
Annual Salary: $320,000 - $405,000 USD
Logistics
- Minimum education: Bachelor’s degree or equivalent combination of education, training, and/or experience
- Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
- Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. Some roles may require more time in offices.
- Visa sponsorship: We do sponsor visas. 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 and we retain an immigration lawyer to help.
How we're different
We work as a single cohesive team on a few large-scale research efforts and value impact over smaller efforts. We host frequent research discussions and value communication skills. Recent research directions include GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Benefits
Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a collaborative office space.