Analysis engineer
3 weeks ago
We are innovating at every level of the stack – from chip, to microcode, to power delivery and cooling, to new algorithms and network architectures at the cutting edge of ML research. Our fully integrated system delivers unprecedented performance because it is built from the ground up for deep learning workloads.
- Build performance models to understand the performance of state of the art and customer models
- Optimize our Kernel micro code and Compiler algorithms to elevate ML model utilization on the Cerebras WSE
- Debug and understand runtime performance on the system and cluster
- Design performance features for upcoming ML architectures to enable highest performance execution on both training and inference
- Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster
- Masters in Electrical Engineering or Computer Science
- Strong background in computer architecture
- Strong analytical and problem solving mindset
- 3+ years of experience in a relevant domain (Computer Architecture, Network Performance, 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
- Exposure to and basic understanding of machine learning is desired
- Any pre-silicon performance validation exposure is a plus but not necessary
People who are serious about software make their own hardware. Members of our team tell us there are five main reasons they joined Cerebras:
- 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
Apply today and become part of the forefront of groundbreaking advancements in AI.
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