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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. We are seeking a Compiler Engineer to help design and implement new features in our low-level compiler toolchain including the compiler mid-end, backend, assembler, and linker targeting individual cores in this unique architecture. You’ll work primarily within the LLVM infrastructure, developing code generation and optimization strategies for both existing and future architectures. This role focuses on generating highly optimized single-core code, foundational to scaling performance across our massively parallel system.
Job Responsibility:
Design and implement low-level compiler components (compiler backend, assembler, linker) targeting single cores
Automate generation of new LLVM targets using high-level architecture description
Identify and develop novel LLVM mid-end and backend passes that leverage architectural features and optimize code generation for performance, including memory usage, instruction scheduling, and register allocation
Analyze performance bottlenecks and iterate on codegen strategies for complex workloads
Work closely with hardware architects, kernel developers, and high-level language designers to ensure end-to-end performance
Participate in technical reviews, design discussions, and collaborative debugging
Requirements:
Bachelor’s, Master’s, PhD, or foreign equivalents in computer science, engineering, or related field
Strong hands-on experience with LLVM, particularly in backend code generation
Two or more years of related work experience on compilers/toolchain development or systems programming
Strong proficiency in C++, especially modern C++ practices
Deep understanding of computer architecture, instruction sets, and memory models
Familiarity with linkers, assemblers, and binary formats
Nice to have:
Exposure to AI/ML workloads and compilers (MLIR, XLA, TVM, etc.)
Understanding of multi-dimensional data representations and vectorized operations
What we offer:
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