At a Glance
- Tasks: Lead the development of reliable AI infrastructure and manage complex technical initiatives.
- Company: Join a pioneering AI company focused on innovative technology and collaboration.
- Benefits: Enjoy competitive pay, health perks, remote work options, and growth opportunities.
- Other info: Dynamic team environment with strong mentorship and career advancement potential.
- Why this job: Make a real impact in AI by building cutting-edge infrastructure for millions of users.
- Qualifications: Expertise in distributed systems and proficiency in systems languages like Rust or Go.
The predicted salary is between 80000 - 100000 € per year.
Requirements
- Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
- Strong proficiency in at least one systems language (e.g., Rust, Go, or Python) and 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
- (Desirable) 8+ years of software engineering experience, including time as a technical lead setting direction for a team
- (Desirable) Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency
- (Desirable) Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines
- (Desirable) Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons
- (Desirable) Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads
- (Desirable) Demonstrated ownership of production reliability for high-throughput, latency-sensitive systems
- (Desirable) Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.)
- (Desirable) Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems
- Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
- Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
- 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
What the job involves
- 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 — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand
- 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
- 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 the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity
- Define infrastructure architecture, ensuring the hardest problems get solved – whether by you directly or by working through others
- Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy
- Establish and evolve operational excellence practices (incident response, post‑mortem culture, on‑call)
- Support the growth of engineers around you through technical mentorship and coaching
Staff Software Engineer (Node Infrastructure) in London employer: Deepstreamtech
At Anthropic, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our commitment to employee growth is evident through our mentorship programmes and opportunities to lead complex technical initiatives, all while working in a dynamic environment that values reliability and cutting-edge technology. Located in a vibrant area, our hybrid work policy allows for flexibility, ensuring that our team can thrive both in the office and remotely.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Software Engineer (Node Infrastructure) in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews by practising common technical questions and scenarios. We recommend doing mock interviews with friends or using platforms that simulate real interview conditions. It’ll boost your confidence and help you shine!
✨Tip Number 3
Show off your skills! If you’ve got projects or contributions to open-source work, make sure to highlight them during interviews. We love seeing practical examples of your expertise, especially in areas like Kubernetes or machine learning.
✨Tip Number 4
Don’t hesitate to apply through our website, even if you think you don’t tick every box. We value diverse experiences and perspectives, so go ahead and throw your hat in the ring. You might just surprise yourself!
We think you need these skills to ace Staff Software Engineer (Node Infrastructure) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Staff Software Engineer. Highlight your experience with distributed systems, cloud platforms, and any relevant programming languages like Rust or Go. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include any hands-on projects or contributions to open-source that demonstrate your expertise in infrastructure and machine learning accelerators. This is your chance to show us what you've built and how it relates to our mission at StudySmarter.
Craft a Compelling Cover Letter:Your cover letter should tell us why you're passionate about this role and how you can contribute to our team. Be sure to mention any leadership experiences and your ability to communicate effectively with stakeholders, as these are key for us.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you're keen on joining the StudySmarter family!
How to prepare for a job interview at Deepstreamtech
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of distributed systems, cloud platforms, and the specific technologies mentioned in the job description. Be ready to discuss your hands-on experience with Kubernetes, Terraform, and any machine learning accelerators you've worked with. This will show that you're not just familiar with the tools but can also apply them effectively.
✨Showcase Your Leadership Skills
Since the role involves leading complex initiatives, prepare examples of past projects where you took charge. Highlight how you built alignment across teams and communicated with stakeholders at various levels. This will demonstrate your ability to lead and collaborate effectively, which is crucial for this position.
✨Prepare for Technical Deep Dives
Expect to dive deep into technical discussions during your interview. Be ready to explain system design trade-offs and your thought process behind decisions you've made in previous roles. Practising common system design questions can help you articulate your expertise clearly and confidently.
✨Emphasise Your Problem-Solving Skills
The job involves tackling challenging problems related to infrastructure and reliability. Prepare to discuss specific instances where you've identified issues and implemented solutions, especially in high-throughput or latency-sensitive environments. This will showcase your analytical skills and your ability to think critically under pressure.
