Publié il y a 3 mois
Cluster Operations Software Engineer
@ Cerebras Systems
Toronto, Ontario
En bref
Cerebras Systems is hiring a Cluster Operations Software Engineer to manage and operate its machine learning compute clusters built around the Wafer-Scale Engine. The role combines operating large-scale AI infrastructure with building the software, monitoring and automation tools that keep it healthy. It is a full-time position based in the SF Bay Area, Toronto or Bangalore, with willingness to join a 24/7 on-call rotation required.
Responsabilités :
- Deploy and debug container-based services using Docker
- Build monitoring, automation and reliability tooling for clusters
- Monitor cluster health and maximize compute capacity
- Provide 24/7 monitoring, support and escalation handling
Résumé des exigences :
- 6 to 8 years managing complex compute infrastructure
- Proficient in Python and Go
- Expertise in distributed systems
- Extensive knowledge of Docker and Kubernetes
- Willingness to participate in 24/7 on-call rotation
Outils et compétences
Source et dates
Site carrière / système de candidatures · ashby
- Date publiée par l’employeur
- 2026-08-13
- 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 | 6 an(s) et plus |
| Heures par semaine | 40 (estimé) |
| Horaire | nuit |
| Déplacements | avion : aucun · route : aucun |
| 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
We are seeking a highly skilled and experienced AI Cluster Operations Engineer to manage and operate our cutting-edge machine learning compute clusters. These clusters would provide the candidate with an opportunity to work with the world's largest computer chip, the Wafer-Scale Engine (WSE), and the systems that harness its unparalleled power.
You will play a critical role in ensuring the health, performance, and availability of our infrastructure, maximizing compute capacity, and supporting our growing AI initiatives. This role requires a deep understanding of Linux-based systems, containerization technologies, and experience with monitoring and troubleshooting complex distributed systems. The ideal candidate is a proactive problem-solver with expertise in large-scale compute infrastructure, dependable and an advocate for customer success.
Responsibilities
Deploy, configure, and debug container-based services using Docker.
Build and own software solutions that power cluster operations, including monitoring platforms, workflow automation systems, operational dashboards, and reliability tooling.
Collaborate with cross-functional teams to translate operational requirements into scalable O&M products and platform capabilities.
Develop APIs, automation services, and integrations that improve operational visibility, incident response, and fleet management across global AI infrastructure.
Manage and operate multiple advanced AI compute infrastructure clusters.
Monitor and oversee cluster health, proactively identifying and resolving potential issues.
Maximize compute capacity through optimization and efficient resource allocation.
Provide 24/7 monitoring and support, leveraging automated tools and performing hands-on troubleshooting as needed.
Handle engineering escalations and collaborate with other teams to resolve complex technical challenges.
Stay up-to-date with the latest advancements in AI compute infrastructure and related technologies.
Skills And Requirements
6-8 years of relevant experience in managing and operating complex compute infrastructure, preferably in the context of machine learning or high-performance computing.
Proficient in Python and Go, with experience building operational platforms, workflow automation systems, and reliability tooling for large-scale infrastructure environments.
Experience and Expertise in distributed systems is a must.
Deep understanding of Linux-based compute systems and command-line tools.
Extensive knowledge of Docker containers and container orchestration platforms like k8s.
Proven ability to troubleshoot and resolve complex technical issues in a timely and efficient manner.
Experience with monitoring and alerting systems.
Should have a proven track record to own and drive challenges to completion.
Excellent communication and collaboration skills.
Ability to work effectively in a fast-paced environment.
Willingness to participate in a 24/7 on-call rotation.
Preferred Skills And Requirements
Operating and Managing large scale AI clusters.
Knowledge of technologies like Ethernet, RoCE, TCP/IP, etc. is desired.
Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure).
Location
SF Bay Area.
Toronto, Canada.
Bangalore, India.
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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