Network Architect

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.

As a Network Architect on the Cluster Architecture Team, you will work closely with the vendors, internal networking teams and industry peers to develop best-in-class interconnect architecture of the current and future generations of the Cerebras AI clusters. You will be responsible for developing proof-of-concept of new network designs and features enabling resilient and reliable network for AI workloads. The role will require cross-functional collaboration and interaction with diverse hardware components (e.g., network devices and the Wafer-Scale Engine) as well as software at several layers of the stack, from host-side networking to cluster-level coordination. The role also requires understanding of network monitoring systems and network debugging methodologies.

• Design AI/ML and HPC Clusters.
• Identify and address performance or efficiency bottlenecks, ensuring high resource utilization, low latency, and high throughput communication.
• Drive technical projects involving multiple teams, various software and hardware components coming together to realize advanced Networking technologies.
• Bring effective communication skills.
• Collaborate with vendors and industry peers to drive network hardware and feature roadmap.
• Represent Cerebras in industry forums.
• Central point of contact for any network reliability issues.

• Ph.D. in Computer Science or Electrical Engineering 10 years industry experience or Master’s in CS or EE 15 years industry experience.
• 8 Years of experience in large scale network designs in WAN or Datacenter.
• Extensive experience debugging networking issues in large distributed systems environment with multiple networking platforms and protocols.
• Experience of managing and leading multi-phase and multi-team projects.
• Networking platforms like Juniper, Arista, Cisco, Open box architectures (Sonic, FOBSS).
• Networking protocols like RoCE, BGP, DCQCN, PFC, Streaming telemetry.
• Familiarity with automation languages like Python, or Go.
• Familiarity with Network visibility and management systems.

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.

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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