Cerebras Systems

Compute Server Platform Architect

Sunnyvale CA or Toronto Canada

Sponsorship not specifiedDetected 97 days ago

PythonC++LinuxMachine LearningLLMsComplianceBudgetingLeadershipCommunication

About the role

As a Compute / Server Platform Architect on the Cluster Architecture Team, you will own the server-side platform architecture that enables Cerebras CS3-based AI clusters (training and inference) to deliver predictable performance, scalability, and reliability.
Our accelerators are network-attached, so the x86 server fleet is a first-class part of the end-to-end system: it runs critical-path runtime functions (for example orchestration, prompt caching, and IO/control services) and must be co-designed with software for token-level latency, throughput, and cost efficiency.
You will translate workload behavior into CPU, memory, IO, PCIe, and host-networking requirements, drive platform evaluations with vendors, and provide technical leadership through qualification and production adoption in close partnership with other function leaders and TPMs.

Own the architecture for all server roles in Cerebras clusters, including definitions of server types, configurations, and lifecycle strategy.
Define and maintain server formulas (counts and ratios per CS-3 count, cluster size, and workload type) including capacity planning and headroom policy.
Develop performance and scaling models
validate with microbenchmarks and workload-level experiments
identify bottlenecks and drive cross-stack fixes.
Lead technical vendor engagements (OEM/ODM and component vendors): influence roadmap, request platform knobs, and drive joint debugging on performance or reliability issues.
Define qualification and acceptance criteria (performance, stability, operability) and partner with the Infrastructure Hardware TPM to execute qualification plans and land changes cleanly into production.
Support bring-up and rare deployment debugging in lab and staging environments
drive root-cause analysis for regressions spanning firmware, drivers, OS, and runtime behavior.
Develop performance and scaling models; validate with microbenchmarks and workload-level experiments; identify bottlenecks and drive cross-stack fixes.

PhD. in Computer Science or Electrical/Computer Engineering and + 8 years industry experience, or Master's/Bachelor's in CS or EE + 10 years industry experience.
5+ years of experience in server platform architecture, systems performance engineering, or large-scale infrastructure design for AI/ML, HPC, or performance-sensitive distributed systems.
Experience reasoning about high-performance IO paths, including NIC behavior at a systems level, RDMA/RoCE concepts, and NVMe performance characteristics.
Familiarity with application and system software (C, C++, Python).

Five Reasons to Join Cerebras in 2026.
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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.
At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry.

This listing is sourced directly from Cerebras Systems's careers page and normalized into a canonical job model.