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Performance Technical Lead Manager
2 months ago
Cerebras has developed a radically new chip and system to dramatically accelerate deep learning applications. Our system runs training and inference workloads orders of magnitude faster than contemporary machines, fundamentally changing the way ML researchers work and pursue AI innovation.
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.
Responsibilities:
- Build performance models to understand the project 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
Requirements:
- Experience managing and technically leading small teams (3-5 people)
- Preference for experience having had grown teams and organizations
- Strong communication and presentation skills
- 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
