Python​/PyTorch Developer — Frontend Inference Compiler

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 global corporations across multiple industries, national labs, and top‑tier healthcare systems. In January, we announced a multi‑year, multi‑million‑dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU‑based hyperscale cloud inference services.

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 unique Software and Hardware combination that sports best inference characteristics in the market while running largest models available.

Cerebras wafer scale inference platform allows running Generative models with unprecedented speed thanks to unique hardware architecture that provides fastest access to local memory, ultra‑fast interconnect and huge amount of available compute.

You will be part of the team that works with 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.

• Analysis of new models from generative AI field and understanding of impacts on compilation stack

• Develop and maintain the frontend compiler infrastructure that ingests PyTorch models and produces an intermediate representation (IR).
• Extend and optimize PyTorch FX / Torch Script / Torch Dynamo
  -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

• 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., Torch Script, 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 Hugging Face 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

• Prior experience contributing to Py Torch ,
  Tensor Flow 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.

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:

Read our blog:
Five Reasons to Join Cerebras in 2025.

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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