Manufacturing Linux Network Engineer

Reposted 4 Days Ago
Sunnyvale, CA, USA
In-Office
Mid level
Artificial Intelligence
The Role
The Manufacturing Linux Network Engineer designs and maintains IT/network infrastructure across manufacturing facilities, ensuring high availability and security. They handle Linux server administration, network configuration, and collaborate with various teams for production systems connectivity.
Summary Generated by Built In

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.

About The Role

We are seeking an experienced Manufacturing Linux / Network Engineer to design, implement, and maintain robust IT and network infrastructure across our manufacturing facilities. The ideal candidate brings deep expertise in Linux systems administration (Red Hat / Rocky Linux), network security (Palo Alto firewalls), storage infrastructure, CI/CD pipelines (Jenkins), and infrastructure automation (Ansible). This role sits at the intersection of enterprise IT and plant-floor operations, and is critical to delivering the high availability, security, and performance that modern manufacturing environments demand.

Responsibilities
  • Design, deploy, and maintain LAN/WAN network infrastructure spanning manufacturing plants, warehouses, cloud providers, and corporate sites.
  • Implement and manage high-speed core switching at 10G and 100G using Arista, Juniper, and other enterprise switching platforms; ensure scalable, resilient fabric design.
  • Configure, troubleshoot, and optimize Layer 2/3 networking (LACP, VLANs, BGP) and security controls (Palo Alto firewalls, VPNs, NAC, IDS/IPS); manage ISP link failover and path redundancy.
  • Deploy, configure, and maintain Linux servers (Red Hat / Rocky Linux) using automation tools including Ansible, MAAS, Foreman, and custom scripting to ensure consistent, repeatable provisioning.
  • Monitor network and system performance — uptime, latency, bandwidth utilization, and capacity — across all sites; proactively detect and resolve issues before they impact
  • Design and maintain redundancy, failover, QoS, and traffic engineering strategies to support 24/7 manufacturing operations and minimize unplanned downtime.
  • Manage structured cabling, Wi-Fi 6/6E wireless infrastructure, and ruggedized networking hardware suited for plant-floor environments.
  • Partner with engineering, automation, OT, and IT security teams to ensure secure and reliable connectivity for production and operational systems.
  • Lead and contribute to greenfield and brownfield IT/OT modernization projects, including network redesigns for new equipment rollouts and facility expansions.
  • Own network documentation including topology diagrams, IP address management (IPAM), and standard operating procedures; keep them current as infrastructure evolves.
  • Provide Tier 2/3 support for network and Linux system incidents at manufacturing sites; participate in on-call rotation for production-critical issues.
Requirements
  • Bachelor’s degree in Computer Science, Information Technology, Electrical Engineering, or a related field.
  • 4+ years of experience in network and Linux infrastructure engineering, preferably in a manufacturing or industrial environment.
  • Deep Linux expertise with Rocky Linux / RHEL, including administration of core infrastructure services: DNS, DHCP, and network storage (NFS).
  • Hands-on experience with Palo Alto Networks firewalls, including policy management, threat prevention, and configuration of active/standby ISP failover links.
  • Demonstrated ability to automate infrastructure at scale; proven track record applying Infrastructure as Code (IaC) best practices using Ansible, Terraform, or equivalent tooling. 
  • Strong knowledge of networking fundamentals: TCP/IP, VLANs, routing protocols (OSPF, BGP), switching, and network security.
  • Experience with enterprise network vendors including Cisco, Arista, and Juniper; familiarity with ruggedized industrial switches (Hirschmann, Cisco IE series, or similar).
  • Knowledge of cybersecurity best practices aligned with NIST frameworks. 
  • Experience with wireless networking (Wi-Fi 6, cellular/private LTE) in industrial or plant-floor settings. 
  • Experience with network monitoring and observability platforms (Grafana, Zabbix, or similar) and on-call alerting integrations such as PagerDuty.
  • Ability to review data center and plant-floor physical designs; experience collaborating with cabling vendors and server rack build teams to implement structured cabling best practices.
  • Comfortable working on the plant floor alongside cross-functional teams including maintenance, engineering, and operations.
  • Strong troubleshooting, documentation, and communication skills. 
  • Able to participate in on-call rotation and respond to after-hours production-critical incidents. 
Preferred Qualifications
  • Experience with Python scripting for network automation, configuration management, and compliance reporting.
  • Experience with cloud connectivity and hybrid network architectures (AWS, Azure, or GCP) in manufacturing contexts.
  • Familiarity with MES platforms and their integration with enterprise IT systems. 
  • Knowledge of structured cabling standards (TIA-568, IEC 11801) and data center operations within manufacturing environments.
  • Experience with SD-WAN solutions for multi-site manufacturing connectivity. 
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:

  1. Build a breakthrough AI platform beyond the constraints of the GPU.
  2. Publish and open source their cutting-edge AI research.
  3. Work on one of the fastest AI supercomputers in the world.
  4. Enjoy job stability with startup vitality.
  5. Our simple, non-corporate work culture that respects individual beliefs.

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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Skills Required

  • Bachelor's degree in Computer Science, Information Technology, Electrical Engineering or related field
  • 4+ years of experience in network and Linux infrastructure engineering
  • Deep Linux expertise with Rocky Linux / RHEL
  • Hands-on experience with Palo Alto Networks firewalls
  • Ability to automate infrastructure using Ansible, Terraform, or similar tools
  • Strong knowledge of networking fundamentals like TCP/IP, VLANs, routing protocols
  • Experience with enterprise network vendors like Cisco, Arista, and Juniper
  • Knowledge of cybersecurity best practices aligned with NIST frameworks
  • Experience with network monitoring platforms (Grafana, Zabbix)

Cerebras Systems Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cerebras Systems and has not been reviewed or approved by Cerebras Systems.

  • Fair & Transparent Compensation Pay is considered competitive for an AI‑hardware firm, and many employees are described as generally happy with compensation. Sentiment indicates compensation is viewed favorably while acknowledging variation by role and seniority.
  • Healthcare Strength Health coverage is described as top quality with medical, dental, and vision included. Premiums are reportedly fully covered for employees in some plans, increasing perceived value.
  • Flexible Benefits Work‑from‑home flexibility is regarded as strong. Flexible arrangements complement standard offerings like vacation, sick leave, and paid holidays.

Cerebras Systems Insights

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The Company
HQ: Sunnyvale, CA
402 Employees
Year Founded: 2016

What We Do

Cerebras Systems is a team of pioneering computer architects, computer scientists, deep learning researchers, functional business experts and engineers of all types. We have come together to build a new class of computer to accelerate artificial intelligence work by three orders of magnitude beyond the current state of the art. The CS-2 is the fastest AI computer in existence. It contains a collection of industry firsts, including the Cerebras Wafer Scale Engine (WSE-2). The WSE-2 is the largest chip ever built. It contains 2.6 trillion transistors and covers more than 46,225 square millimeters of silicon. The largest graphics processor on the market has 54 billion transistors and covers 815 square millimeters. In artificial intelligence work, large chips process information more quickly producing answers in less time. As a result, neural networks that in the past took months to train, can now train in minutes on the Cerebras CS-2 powered by the WSE-2. Join us: https://cerebras.net/careers/

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