
Software Engineer, Cluster Deployment at Cerebras Systems (Sunnyvale, CA)
Cerebras Systems· Sunnyvale, CA·
Role details
Cerebras Systems at a glance
Cerebras builds wafer-scale AI chips, the largest ever made, plus the supercomputers and fast inference cloud that run on them.
Cerebras designs the Wafer-Scale Engine, the largest computer chip ever built, and sells it as on-premises CS-3 supercomputers and as a pay-as-you-go inference and training cloud. Its pitch is speed: keeping a whole model on one piece of silicon delivers AI inference the company says runs up to 15x faster than GPU clusters.
$5.55B (IPO); ~$2.7B raised privately beforehand raised · latest: IPO · ~$5.55B · May 2026 (Nasdaq: CBRS, priced at $185) · backed by Sam Altman, Ilya Sutskever, Andy Bechtolsheim, Adam D'Angelo
Job description
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.
About the Role
We build and operate the software systems that deploy, validate, and manage AI compute clusters across data centers worldwide for the world’s fastest AI Inference. Our work turns complex bare-metal infrastructure into repeatable, automated deployment flows spanning server provisioning, network configuration, Kubernetes bring-up, health validation, and operational handoff. As a Software Engineer on the Cluster Deployment Automation team, you will help build the pushbutton tooling that makes large-scale cluster deployments faster, safer, and more reproducible. This role is designed for talented engineers passionate about learning through hands-on work with Python, Bash, Ansible, Linux, bare-metal servers, networking equipment, Kubernetes, and observability systems while learning how production AI infrastructure is built and operated at scale.
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.
Basic Qualifications
- 2+ years of mid- to large-scale data center deployment
- Strong fundamentals in Python and Bash, with 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.
- CS, ECE, or related technical degree, or equivalent practical experience.
- Curiosity, strong problem-solving instincts, and willingness to work hands-on with real infrastructure.
Preferred 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.
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. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
Why work at Cerebras Systems
- Culture: “Extraordinary people, breakthrough innovation, global impact” – the company highlights collaborative, low‑overhead teams with little bureaucracy.
- Work environment: Hybrid/office with locations in Sunnyvale, San Diego, Toronto, and Bangalore. Inclusive and flexible policy.
- Perks: Premium medical/dental/vision, life insurance, generous vacation, 401(k) and Group RRSP retirement plans, daily catered meals, healthy snacks, family‑friendly events (including CEO’s famous BBQ).
- Engineering focus: Tackling fundamental challenges in chip design, system software, compiler technology, and ML workflows. Positions range from hardware (Design Verification, Manufacturing) to software (SRE, Compiler, Cloud).
- Philanthrophy: Supports local communities and hosts students from around the world for Q&A.