About the job
At Cerebras Systems, we are revolutionizing AI computing by developing the world’s largest AI chip, which is 56 times larger than traditional GPUs. Our innovative wafer-scale architecture provides the computational power equivalent to dozens of GPUs on a single chip, simplifying programming to the level of a single device. This unique approach enables us to achieve unparalleled training and inference speeds, allowing machine learning practitioners to run large-scale ML applications without the complexity of managing multiple GPUs or TPUs.
Our esteemed clientele includes leading model laboratories, prominent global enterprises, and forward-thinking AI-native startups. Notably, OpenAI has entered a multi-year partnership with Cerebras to leverage 750 megawatts of scale, enhancing critical workloads with ultra-high-speed inference.
With our groundbreaking wafer-scale architecture, Cerebras Inference delivers the fastest Generative AI inference solution globally, outperforming GPU-based hyperscale cloud inference services by over tenfold. This dramatic increase in speed is transforming how users experience AI applications, facilitating real-time iterations and enhancing intelligence through additional agentic computation.
Location: Toronto / Sunnyvale
We are seeking a highly technical, hands-on engineering leader for our Inference Service Platform. In this role, you will guide a high-performing team to address a critical challenge: scaling large language model (LLM) inference on Cerebras’ advanced compute clusters and delivering a world-class, on-premise solution for enterprise customers. You will establish the technical vision while maintaining close engagement with the code, focusing on architecting highly reliable and low-latency distributed systems. If you possess proven expertise in distributed systems and scaling modern model-serving frameworks, we encourage you to apply.
