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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 global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.

As an Applied Data Center Design Engineer, you’ll own the “last mile” of cluster architecture - transforming high-level design specifications into efficient, real-world deployment blueprints for servers, storage, networking, and cabling.

You’ll be responsible for customizing data center and rack-level designs based on specific cluster requirements - adapting layouts, power, and connectivity to optimize performance, scalability, and reliability. When real-world constraints like space, power, or supply chain limitations arise, you’ll make smart trade-offs to deliver practical, deployable solutions.

This role combines hands-on problem solving with automation and tooling - you’ll also help design and build the frameworks that make each new deployment iteration faster, smarter, and more consistent across sites.

It’s a great opportunity for someone early in their career who enjoys working at the intersection of hardware, software, and operations, and wants to shape the foundation of large-scale compute infrastructure.

• Translate cluster and rack-level design specifications into deployable blueprints for servers, storage, networking, and cabling.
• Customize rack-level designs to meet unique cluster requirements, ensuring power, thermal, and network connectivity are optimized for each deployment.
• Collaborate with operations team to validate and adapt designs based on site-specific constraints (e.g., power, cooling, space, logistics).
• Identify and implement automation and tooling to streamline BOM generation and design validation.
• Participate in data center deployment reviews, ensuring alignment between design intent and implementation.
• Support issue triage and root cause analysis for deployment-related or physical integration problems.

• Bachelor’s or Master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field — or equivalent practical experience.
• 1–3 years of experience in infrastructure engineering, data center design, or systems deployment, creating rack elevations, bill of materials (BOMs), and port/cable maps.
• Familiarity with servers, networking, and storage hardware.
• Basic proficiency in scripting or automation (e.g., Python, PowerShell, or Bash).
• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication and teamwork skills across multiple engineering disciplines.

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 2025.

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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