Distributed Software Engineer
Cerebras is hiring a Distributed Software Engineer for a remote role open to applicants in Canada. Level rates it ; you can apply on Cerebras.
Level's read on this job
- Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
- The posting lists this role as remote.
- Tools and skills the posting cites include OpenAI, Go and Python.
- Level classifies it as a senior role.
- Level lists 121 other open roles at Cerebras.
AI in this role
Distributed Software Engineer to build and operate infrastructure and automation for large-scale AI training and inference clusters.
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Role
The Cluster engineering team owns the software that turns thousands of wafers, servers, and switches into a cloud that stays up, stays busy, and stays debuggable. We stand clusters up from bare metal, schedule training and inference workloads across the fleet, keep it healthy, and make it observable to users, operators, and increasingly to AI agents. The stack is Go and Python on Kubernetes, running both on-premise deployments and our own cloud.
Responsibilities
· Declarative, CRD-driven automation of bare-metal networking, OS, and application software across clusters of Cerebras systems, servers, and switches, built to reconcile thousands of nodes
· Push-button cluster install, upgrade, and security patching with real downtime budgets, gated by canaries
· Kubernetes operators that schedule large inference workload: resource locks, priority queues, network topology, and health-aware placement
· gRPC control-plane services, authorization, admission webhooks, and quota policy for a multi-tenant fleet
· Metrics and log pipelines with purpose-built exporters for wafer-scale systems, servers (Redfish, IPMI), and network fabric (gNMI, sFlow), on Prometheus and Grafana, with SLOs and alerting
· Failure detection, HA control planes, and automated recovery, plus the CLIs, APIs, and MCP gateway that expose the fleet to users, operators, and AI agents
Skills and Qualifications
· 5+ years building and operating production distributed systems or infrastructure software
· Production-quality Go and Python
· Real Kubernetes depth: you have written or debugged controllers and operators, and you understand CRDs, reconciliation semantics, informer caches, admission webhooks, and RBAC
· Strong debugging skills across distributed systems, Linux, and networking
· Prometheus and Grafana as a practitioner: PromQL, exporter design, cardinality discipline, useful alerts
· Strong self-driving capability. This environment is large, fast-moving, and not fully documented, so we need engineers who build their own context, decide, and drive work across team boundaries. Learning speed matters more here than familiarity with our stack.
· Demonstrated adoption of AI in your engineering workflow: active use of coding agents, a view on where they help and where they mislead, and the rigor to verify what they produce.
· Nice to have: bare-metal or HPC fleet operations, scheduler internals, RDMA/RoCE and eBPF networking, Ceph or NVMe-oF, etcd and HA upgrades, inference serving stacks. ML research experience is not required.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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How we rate this
Distributed Software Engineer at Cerebras rates 80 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $168k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where networking was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, AI Research, Distributed Systems, Infrastructure, and Networking. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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