Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top 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.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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.
Role Summary
The AI Infrastructure Operations Engineer (SiteOps) is an entry-level individual contributor role focused on the deployment, bring-up, monitoring, and first-line troubleshooting of Cerebras AI infrastructure in data center environments. The role supports CS systems, cluster server hardware, cluster networking hardware, and hardware telemetry and monitoring tools.
Role Mandate
Support reliable operation and scale-out of Cerebras AI clusters by executing defined hardware bring-up and validation procedures, monitoring telemetry, performing first-line troubleshooting, and escalating issues using established workflows.
Core Responsibilities
• Execute power-on sequencing, readiness checks, and validation tests
• Monitor hardware telemetry, alerts, and dashboards
• Perform first-line troubleshooting and structured escalation
• Collect logs, telemetry, and observations during incidents
Incident Support & Tooling
• Use existing monitoring, telemetry, and incident tracking tools
• Provide feedback on tooling and process gaps
Learning & Development
• Learn cluster hardware and networking fundamentals
• Shadow senior engineers during complex debugging
• Progress toward independent ownership of defined workflows
Explicit Non-Responsibilities
• No final escalation authority
• No ownership of cluster architecture, hardware design, or tooling architecture
Required Qualifications
Bachelor’s degree in a relevant engineering field or equivalent experience; 0–3 years experience in hardware operations, systems engineering, or datacenter environments; basic familiarity with server hardware, networking fundamentals, and Linux systems.
Preferred Qualifications
Internship or early-career experience in datacenter or hardware lab environments; exposure to monitoring or telemetry systems; comfort working in data centers.
What Success Looks Like
Consistent and correct execution of hardware bring-up procedures, early identification and escalation of issues, improving documentation quality, and clear progression toward more independent operational responsibility.
Career Path
This role progresses naturally toward Senior and Principal IC roles within AI Infrastructure Operations (SiteOps), with an optional management track.
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:
Read our blog: Five Reasons to Join Cerebras in 2026.
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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