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 

• Bring up new features in the performance/power model
• Perform comprehensive PPA trade-offs for new architectural features
• Extract insights for new features and  micro-architecture power efficiency
• Profile workloads, identify bottlenecks and project competition performance for benchmarking 
• Engage with SW teams for end-end application level modeling at cluster level
• Identify kernel level HW acceleration level opportunities

Skills & Qualifications

• Masters/PhD in Electrical/Computer Engineering 
• 10+ years of experience across performance analysis and modeling across GPUs, CPUs or accelerator products
• Strong background in computer architecture and key high level architectural trade-offs
• Comfortable standing up new performance models from scratch in Python or similar analytical environments
• Exposure to micro-code (kernel) performance bottlenecks and optimization techniques
• Good understanding of how high level workloads map to underlying micro-architecture is desired
• Understanding of basic ML workload profiling techniques and model network architecture is preferred

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection  point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

1. Build a breakthrough AI platform beyond the constraints of the GPU
2. Publish and open source their cutting-edge AI research
3. Work on one of the fastest AI supercomputers in the world
4. Enjoy job stability with startup vitality
5. Our simple, non-corporate work culture that respects individual beliefs

Read our blog: Five Reasons to Join Cerebras in 2024.

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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