NewGrad-MLStackOptimizationEngineer

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 top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Job Overview We are seeking a highly skilled Compiler Engineer with a passion of optimizing compiler technologies for AI workloads. You will be an integral part of our software compiler stack team, focusing on enhancing our compiler to fully leverage the unique capabilities of our CS3 system. Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications. Key Responsibilities Design, develop, and optimize compiler technologies for AI chips using LLVM and MLIR frameworks. Identify and address performance bottlenecks, ensuring optimal resource utilization and execution efficiency. Work with the machine learning team to integrate compiler optimizations with AI frameworks and applications. Contribute to the advancement of compiler technologies by exploring new ideas and approaches. Qua