Publié il y a 2 mois
Distributed Software Engineer
@ Cerebras Systems
Toronto, Ontario
En bref
Cerebras Systems is hiring a Distributed Software Engineer for its Cluster engineering team, which builds the software that stands up, schedules, monitors and recovers large AI clusters. The work involves Go and Python on Kubernetes, building operators, control-plane services and observability pipelines, across on-premise and cloud deployments. The posting states a full-time employment type and a requirement of 5+ years of production distributed systems experience, but gives no salary, location or schedule.
Responsabilités :
- Build declarative, CRD-driven automation for bare-metal clusters
- Develop Kubernetes operators for large inference workload scheduling
- Create metrics and log pipelines with Prometheus and Grafana
- Design failure detection, HA control planes and automated recovery
- Build CLIs, APIs and MCP gateway for users and AI agents
Résumé des exigences :
- 5+ years building production distributed systems or infrastructure software
- Production-quality Go and Python
- Deep Kubernetes experience with controllers, operators and CRDs
- Strong debugging across distributed systems, Linux and networking
- Practitioner-level Prometheus and Grafana skills
- Demonstrated use of AI coding agents in engineering workflow
Outils et compétences
Source et dates
Site carrière / système de candidatures · ashby
- Date publiée par l’employeur
- 2026-09-08
- Première détection par notre source
- 2026-10-08
- Mise à jour du dossier source
- 2026-10-09
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Senior |
| Domaine | Développement logiciel |
| Expérience | 5 an(s) et plus |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau, Chez les clients |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Cerebras Systems
Profil d’entreprise sauvegardé
Renseignements historiques provenant d’un profil The Jobs API sauvegardé (champs LinkedIn/Crunchbase). Ils ne sont pas vérifiés en temps réel; les chiffres peuvent avoir changé. Les valeurs manquantes restent inconnues.
The World's Fastest AI Inference
Description complète de l’entreprise
Cerebras Systems is the world's fastest AI inference. We are powering the future of generative AI. We’re a team of pioneering computer architects, deep learning researchers, and engineers building a new class of AI supercomputers from the ground up. Our flagship system, Cerebras CS-3, is powered by the Wafer Scale Engine 3—the world’s largest and fastest AI processor. CS-3s are effortlessly clustered to create the largest AI supercomputers on Earth, while abstracting away the complexity of traditional distributed computing. From sub-second inference speeds to breakthrough training performance, Cerebras makes it easier to build and deploy state-of-the-art AI—from proprietary enterprise models to open-source projects downloaded millions of times. Here’s what makes our platform different: 🔦 Sub-second reasoning – Instant intelligence and real-time responsiveness, even at massive scale ⚡ Blazing-fast inference – Up to 100x performance gains over traditional AI infrastructure 🧠 Agentic AI in action – Models that can plan, act, and adapt autonomously 🌍 Scalable infrastructure – Built to move from prototype to global deployment without friction Cerebras solutions are available in the Cerebras Cloud or on-prem, serving leading enterprises, research labs, and government agencies worldwide. 👉 Learn more: www.cerebras.ai Join us: https://cerebras.net/careers/
- Abonnés LinkedIn
- 119 613
- Personnes associées sur LinkedIn
- 970
- Bureaux déclarés
- 1237 E Arques Ave, Sunnyvale, California 94085, US
- 150 King St W, Toronto, Ontario M5H 1J9, CA
- Tokyo, JP
- Bangalore, IN
- Catégories d’activité
- Semiconductor
- Artificial Intelligence
- Software
- Hardware
- RISC
- Artificial Intelligence (AI)
- AI Infrastructure
- Computer
- Autres noms enregistrés
- Cerebras Systems
- Cerebras
- Spécialités
- artificial intelligence
- deep learning
- natural language processing
- inference
- machine learning
- llm
- AI
- enterprise AI
- and fast inference
- Le profil indique une agence de recrutement
- Non
- Investissement total déclaré
- 4 674 771 259
La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.
Cerebras Systems is the world's fastest AI inference. We are powering the future of generative AI. We’re a team of pioneering computer architects, deep learning researchers, and engineers building a new class of AI supercomputers from the ground up. Our flagship system, Cerebras CS-3, is powered by the Wafer Scale Engine 3—the world’s largest and fastest AI processor. CS-3s are effortlessly clustered to create the…
| Champ | Valeur |
|---|---|
| Secteur | Semiconductor Manufacturing |
| Taille | 501-1,000 employees |
| Siège social | Sunnyvale, California |
| Type d’organisation | Privately Held |
| Spécialités | artificial intelligencedeep learningnatural language processinginferencemachine learningllmAIenterprise AIand fast inference |
| Offres sur Jobsy | 41 |
| Voir la page |
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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