New college grad software engineer building and improving functional and pipeline-accurate simulators in C++ for Cerebras' wafer-scale AI engine. Requires strong C++ and computer architecture knowledge to support hardware/software co-development across kernel, compiler, and verification teams.
Salary not listed
On-siteEntry levelEmbedded Engineering
About the role
Responsibilities
Develop and maintain simulator infrastructure in C++ for next-generation WSE systems.
Contribute to both functional simulation (architectural correctness, instruction behavior, and state and memory semantics) and pipeline-accurate simulation (execution behavior, bottleneck analysis, and performance visibility).
Build features and tooling that improve kernel developer visibility into correctness and performance.
Work with Design Verification and architecture teams to align simulator behavior with hardware specifications and validate design correctness.
Build and maintain strong unit, integration, and regression test coverage for simulator quality.
Improve simulator runtime performance, scalability, and usability for internal engineering workflows.
Debug complex issues that span simulator models, kernels, compiler/runtime interactions, and hardware assumptions.
Contribute to code reviews, documentation, and continuous improvement of engineering workflows.
Skills & Qualifications
Bachelor's or Master's degree (or equivalent) in Computer Science, Computer Engineering, or a related field.
Strong C++ programming skills and software engineering fundamentals.
Solid understanding of computer architecture concepts, including instruction execution, memory systems, and microarchitecture basics.
Strong debugging, analytical, and problem-solving skills.
Ability to collaborate effectively across software and hardware teams.
Preferred Skills & Qualifications
Familiarity with architectural, functional, or performance modeling.
Experience with test automation, regression systems, and CI pipelines.
Exposure to Python or scripting for tooling and automation.
Familiarity with parallel systems, accelerators, or ML/HPC workloads.
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