Job Description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.



Cerebras' current customers include global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.

About the Role:

Would you like to participate in creating the fastest Generative Models inference in the world? Join the Cerebras Inference Team to participate in development of unique Software and Hardware combination that sports best inference characteristics in the market while running largest models available.



Cerebras wafer scale inference platform allows running Generative models with unprecedented speed thanks to unique hardware architecture that provides fastest access to local memory, ultra-fast interconnect and huge amount of available compute.



You will be part of the team that works with latest open and closed generative AI models to optimize for the Cerebras inference platform. Your responsibilities will include working on model representation, optimization and compilation stack to produce the best results on Cerebras current and future platforms.

Job responsibilities:

Analysis of new models from generative AI field and understanding of impacts on compilation stack Implementation of compiler and frontend features to support new models, improve inference characteristics and Cerebras user experience Collaboration with other teams throughout feature implementation Research on new methods for model optimization to improve Cerebras inference

Requirements:

Degree in Engineering, Computer Science, or equivalent in experience and evidence of exceptional ability Strong experience working with Python and C++ languages Experience working with PyTorch and HuggingFace Transformers library Knowledge and experience working with Large Language Models (understanding Transformer architecture variations, generation cycle, etc.) Knowledge of MLIR based compilation stack is a plus


#

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:



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.