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.
Cerebras is building a team of exceptional people to work together on big problems. Join us!
About The Role
As a Runtime Engineer, you will directly impact the performance at which deep learning models are trained on our “distributed systems” hardware and be responsible for enabling next-generation AI applications that require substantial computational capabilities. In this position, you will develop algorithms for execution, acceleration, partitioning, and routing of communication for dataflow graphs on a massively parallel, multi-core architecture.
Specific responsibilities may include:
Requirements
Preferred
Term Length
Please apply to the job with BOTH your resume and transcript (official or unofficial).
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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