About the job
Cerebras Systems is at the forefront of AI technology, developing the world’s largest AI chip that is 56 times larger than conventional GPUs. Our innovative wafer-scale architecture delivers the computational power of dozens of GPUs within a single chip, simplifying programming and enhancing performance. This unique capability enables Cerebras to provide unparalleled training and inference speeds, allowing machine learning practitioners to execute large-scale ML applications seamlessly without the complexities of managing extensive GPU or TPU infrastructures.
Cerebras serves a diverse clientele, including top-tier model labs, global enterprises, and pioneering AI-native startups. OpenAI has recently partnered with Cerebras to leverage 750 megawatts of power, significantly enhancing key workloads through ultra high-speed inference.
Our cutting-edge wafer-scale architecture has made Cerebras Inference the fastest Generative AI inference solution globally, achieving speeds over ten times faster than GPU-based hyperscale cloud inference services. This revolutionary speed is transforming the user experience of AI applications, facilitating real-time iteration and boosting intelligence through enhanced computational capabilities.
- Characterize and enhance the performance and reliability of advanced ML hardware/software systems, focusing on minimizing power and thermal fluctuations.
- Analyze ML workloads, software kernels, and hardware architecture for their power and performance impacts, synthesizing high-level insights across these layers.
- Develop innovative software solutions to enhance system performance and efficiency.
