The opportunity
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
What you'll do
Bring up and optimize performance on new generations of the Cerebras WSE.
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.
Bachelors / Masters / PhD in Electrical Engineering or Computer: Science. Strong background in computer architecture.
What they're looking for
- Exposure to and understanding of low-level deep learning / LLM math.
- Strong analytical and problem-solving mindset.
- + years of experience in a relevant domain (Computer Architecture, CPU/GPU: Performance, Kernel Optimization, HPC).
- Experience working on CPU/GPU simulators.
