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Cerebras

AI accelerator hardware replacing GPUs

Software Engineer - Cluster Deployment

DevOps EngineeringConfirmed live in the last 24 hours
Full-timeSunnyvale, CA, USANo salary listedHybrid

About the Job

Requirements

  • At least 2 years of mid- to large-scale data center deployment experience.
  • Strong fundamentals in Python and Bash, including the ability to write scripts and small programs.
  • Basic Linux experience, including command-line usage, processes, filesystems, and disk troubleshooting.
  • Working knowledge of Git, including branching, commits, pull requests, and code review.
  • A degree in Computer Science, ECE, or a related technical field, or equivalent practical experience.
  • Curiosity, strong problem-solving instincts, and willingness to work hands-on with real infrastructure.

Responsibilities

  • Develop and maintain automation for deployment workflows, including provisioning, configuration, validation, and operational handoff.
  • Turn manual deployment steps into tested, repeatable pushbutton workflows.
  • Participate in hands-on cluster deployments to build practical debugging and operational expertise.
  • Troubleshoot issues across Linux systems, bare-metal servers, networking, storage, Kubernetes, and connectivity.
  • Contribute to infrastructure-as-code and GitOps workflows using tools such as Terraform, Ansible, pull requests, and code review.
  • Add health checks, observability, dashboards, and validation logic to improve deployment reliability.
  • Partner with networking, infrastructure, security, and operations teams to deliver secure and reproducible data center deployments.

Desired Qualifications

  • Networking fundamentals, including VLANs and routing basics; exposure to BGP, switch configuration, or Arista EOS automation is a plus.
  • Kubernetes experience or familiarity.
  • Infrastructure-as-code and GitOps experience, including Terraform, Ansible, and PR-based change control.
  • Bare-metal provisioning concepts such as PXE, DHCP, iPXE, Redfish, IPMI, and BMC management.
  • Observability experience with Prometheus or Grafana.
  • API design and client-server architecture.
  • Automation side projects or open-source contributions.

About the Company

Cerebras

AI accelerator hardware replacing GPUs

Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company's goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.

Company size
501-1,000
Company stage
IPO
Headquarters
Sunnyvale, CA
Founded
2016

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