Compiler Engineer

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. We are seeking a Compiler Engineer to help design and implement new features in our CSL language and compiler. CSL (Cerebras Software Language) is a Zig-like language that is used within and outside the company to program our wafer-scale engine (WSE). The language provides high-level abstractions to ease programming the wafer WSE and provides low-level access to the internals of the hardware to enable efficient utilization of the hardware. The compiler uses MLIR infrastructure to lower CSL to LLVM IR which is then lowered by a separate LLVM mid-end/backend into executables.