Staff Python / PyTorch Developer — Frontend Inference Compiler - Dubai

About the Role

Would you like to participate in creating the fastest Generative Models inference in the world? Join the Cerebras Inference Team to participate in development of a unique software and hardware combination that offers best inference characteristics in the market while running the largest models available.

Cerebras wafer scale inference platform enables running Generative models with unprecedented speed thanks to a hardware architecture that provides fastest access to local memory, ultra-fast interconnect, and a large amount of compute.

You will be part of the team that works with the latest open and closed generative AI models to optimize for the Cerebras inference platform. Your responsibilities will include working on model representation, optimization, and compilation stack to produce the best results on Cerebras current and future platforms. Responsibilities • Analysis of new models from the generative AI field and understanding of impacts on the compilation stack • Develop and maintain the frontend compiler infrastructure that ingests PyTorch models and produces an intermediate representation (IR) • Extend and optimize PyTorch FX / TorchScript / TorchDynamo -based tooling for graph capture, transformation, and analysis • Work with ML and compiler teams to ensure fidelity and performance parity with native PyTorch • Collaboration with other teams throughout feature implementation • Research on new methods for model optimization to improve Cerebras inference Qualifications • Degree in Engineering, Computer Science, or equivalent in experience and evidence of exceptional ability • Strong Python programming skills and in-depth experience with PyTorch internals (e.g., TorchScript, FX, or Dynamo) • Solid understanding of computational graphs, tensor operations, and model tracing • Experience building or extending compilers, interpreters, or ML graph optimization frameworks • Familiarity with C++ extensions, LLVM, MLIR, or other IR-based compiler infrastructures • Experience working with PyTorch and HuggingFace Transformers library • Knowledge and experience working with Large Language Models (understanding Transformer architecture variations, generation cycle, etc.) • Knowledge of MLIR based compilation stack is a plus Preferred Qualifications • Prior experience contributing to PyTorch , TensorFlow XLA , TVM , ONNX , or similar compiler stacks • Knowledge of hardware accelerators , quantization , or runtime scheduling • Experience with multi-target inference compilation (e.g., CPU, GPU, custom ASICs) • Understanding of numerical precision trade-offs and operator lowering • Contributions to open-source ML compiler projects Why Join 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 2025. Apply today

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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