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# ML Systems Performance Engineer

- **Company:** Cerebras Systems
- **Location:** United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** C++ (Programming Language), Profiling, Software Debugging, Python (Programming Language), Machine Learning, Large Language Models, Deep Learning, Information Technology, Machine Learning Operations
- **Published:** July 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=d975993fe1841cf8

## About the Role

* Bachelors / Masters / PhD in Electrical Engineering or Computer Science.
 * Strong background in computer architecture.
 * Exposure to and understanding of low-level deep learning / LLM math.
 * Strong analytical and problem-solving mindset.
 * 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).
 * Experience working on CPU/GPU simulators.
 * Exposure to performance profiling and debug on any system pipeline.
 * Comfort with C++ and Python.

## Description

Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics., * Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.

 * Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.
 * Debug and understand runtime performance on the system and cluster.
 * Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.


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