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Staff LLVM Compiler Engineer
Исключительная возможность работать над революционным железом в компании-партнере OpenAI. Высокий престиж и работа на переднем крае технологий компенсируют высокую сложность задач.
Сложность вакансии
Роль требует экспертных знаний в области LLVM и архитектуры процессоров. Работа с уникальным 'wafer-scale' железом значительно сложнее стандартных задач по оптимизации под x86 или ARM.
Анализ зарплаты
Для позиции уровня Staff в Кремниевой долине и Канаде в сфере системного программирования и ИИ-железа, предлагаемая роль соответствует верхнему сегменту рынка. Компании уровня Cerebras обычно предлагают конкурентные пакеты, включающие значительную долю опционов (RSU).
Сопроводительное письмо
I am writing to express my strong interest in the Staff LLVM Compiler Engineer position at Cerebras Systems. With extensive experience in LLVM backend development and a deep passion for high-performance computer architecture, I am excited by the opportunity to optimize code generation for the world's largest AI chip. My background in developing custom LLVM targets and implementing sophisticated optimization passes aligns perfectly with your mission to deliver industry-leading inference speeds.
Throughout my career, I have focused on bridging the gap between high-level software requirements and low-level hardware constraints. I am particularly drawn to Cerebras because of your unique wafer-scale architecture, which presents fascinating challenges in instruction scheduling and memory management that go far beyond traditional GPU constraints. I am confident that my expertise in modern C++ and compiler toolchains will allow me to contribute immediately to the performance and scalability of your AI platform.
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Откликнитесь в cerebrassystems уже сейчас
Присоединяйтесь к команде, создающей будущее ИИ-вычислений на базе уникальной архитектуры Cerebras!
Описание вакансии
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.
Location Options: Sunnyvale, Toronto, or Vancouver
About the Role
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.
Responsibilities
- 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.
Preferred
- Exposure to AI/ML workloads and compilers (MLIR, XLA, TVM, etc.).
- Understanding of multi-dimensional data representations and vectorized operations.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
- 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.
Read our blog: Five Reasons to Join Cerebras in 2026.
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer.We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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Навыки
- LLVM
- C++
- Computer Architecture
- Assemblers
- Linkers
- Code Generation
- Instruction Scheduling
- Register Allocation
- MLIR
- XLA
- TVM
Возможные вопросы на собеседовании
Проверка глубины знаний внутреннего устройства LLVM.
Расскажите о вашем опыте реализации кастомного бэкенда в LLVM: с какими основными трудностями вы столкнулись при описании системы команд (TableGen)?
Важно для оптимизации производительности на специфичном железе Cerebras.
Как бы вы подошли к реализации специфичного для архитектуры алгоритма распределения регистров, если стандартные жадные алгоритмы LLVM показывают плохие результаты?
Cerebras фокусируется на ИИ-вычислениях.
Каков ваш опыт работы с MLIR и как, по вашему мнению, он может упростить интеграцию высокоуровневых ИИ-фреймворков с низкоуровневым кодогенератором?
Проверка навыков системного программирования.
Опишите процесс линковки для кастомной архитектуры: какие изменения в формате объектных файлов могут потребоваться для поддержки огромного количества ядер?
Оценка навыков отладки сложных систем.
Как вы отлаживаете ошибки в оптимизационных пассах, которые проявляются только на специфических граничных случаях в сгенерированном машинном коде?
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