Cerebras
Cluster Operations Software Engineer
Part remote, part office, you need to live within commuting distance of a named location.
Hybrid · Sunnyvale, CA
Employer listed it 6 weeks ago · Added today
Been open since 6 weeks ago, still checked daily, but it has been live a while.
Salary
Not stated
Location
Hybrid · Sunnyvale, CA
Timezone
Not stated
Contract
Full-time
Experience
Senior
Category
Software
This employer didn't state pay. Jobs like this usually pay around $175k–$230k a year, a typical range taken from 595 senior-level software roles on Nomaders that do state pay. It's a guide, not an offer.
Remote flexibility
Hybrid
This role is only partly remote, the employer expects time in the office around Sunnyvale, CA, Toronto, CAN, Bengaluru, IND, Hybrid, so you need to live within commuting distance.
What the employer says
- Source listing states candidate location: "Sunnyvale, CA, Toronto, CAN, Bengaluru, IND, Hybrid"
- Listing mentions "Hybrid"
What Nomaders makes of it
- Not suitable if you plan to move between countries
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
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.
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.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, hybrid, matches where you plan to live and work.
- 2Tailor your CV to the role at Cerebras, mentioning your remote working experience.
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 22h ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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