Python / PyTorch Developer — Frontend Inference Compiler – Dubai

20 Minutes ago • All levels
Research Development

Job Description

Join the Cerebras Inference Team to develop unique software and hardware for the world's fastest Generative Models inference. You will optimize generative AI models for the Cerebras inference platform, working on model representation, optimization, and compilation stacks to achieve superior results on current and future platforms. This role involves leveraging Cerebras' wafer-scale architecture for unprecedented speed and efficiency in large-scale ML applications.
Good To Have:
  • Prior experience contributing to PyTorch, TensorFlow XLA, TVM, ONNX RT, 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
Must Have:
  • Analyze new generative AI models and their impact on the compilation stack
  • Develop and maintain model definition framework for large language models based on PyTorch and Cerebras dialects
  • Develop and maintain the frontend compiler infrastructure for PyTorch models to produce intermediate representation (IR)
  • Extend and optimize PyTorch FX / TorchScript / TorchDynamo-based tooling for graph capture, transformation, and analysis
  • Collaborate with other teams on feature implementation
  • Research new methods for model optimization to improve Cerebras inference
  • Strong Python programming skills and in-depth experience with PyTorch internals (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
  • Experience working with PyTorch and HuggingFace Transformers library
  • Knowledge and experience working with Large Language Models (Transformer architecture variations, generation cycle)
  • Strong C++ programming skills
  • Knowledge of MLIR based compilation stack
Perks:
  • Build a breakthrough AI platform beyond the constraints of the GPU
  • Publish and open source cutting-edge AI research
  • Work on one of the fastest AI supercomputers in the world
  • Enjoy job stability with startup vitality
  • Simple, non-corporate work culture that respects individual beliefs

Add these skills to join the top 1% applicants for this job

data-structures
talent-acquisition
cpp
game-texts
pytorch
python
tensorflow
machine-learning

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.

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 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.

Responsibilities:

  • Analysis of new models from generative AI field and understanding of impacts on compilation stack
  • Develop and maintain model definition framework that consists of model building blocks to represent large language models based on PyTorch and Cerebras dialects ready to be deployed on Cerebras hardware.
  • 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.
  • 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.
  • Experience working with PyTorch and HuggingFace Transformers library
  • Knowledge and experience working with Large Language Models (understanding Transformer architecture variations, generation cycle, etc.)
  • Strong C++ programming skills.
  • Knowledge of MLIR based compilation stack

Preferred Qualifications

  • Prior experience contributing to PyTorch, TensorFlow XLA, TVM, ONNX RT, 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

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:

1. Build a breakthrough AI platform beyond the constraints of the GPU.

2. Publish and open source their cutting-edge AI research.

3. Work on one of the fastest AI supercomputers in the world.

4. Enjoy job stability with startup vitality.

5. Our simple, non-corporate work culture that respects individual beliefs.

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

Apply today and become part of the forefront of groundbreaking advancements in AI!

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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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