Python / PyTorch Developer — Frontend Inference Compiler – Dubai

Cerebras Systems; United Arab Emirates; On-site; AED 150,000 - 200,000; Full time

Job summary

A leading AI technology firm in Dubai is seeking a Python / PyTorch Developer for frontend inference compiler development. You will analyze generative models and enhance compiler infrastructure to optimize performance on unique hardware. The ideal candidate has a degree in engineering or computer science and strong Python and PyTorch skills, with knowledge of compiler technology. This role offers an innovative environment focused on groundbreaking advancements in AI.

Benefits

Inclusive work culture

Job stability with startup vitality

Opportunity to publish and open source AI research

Qualifications

• Strong Python programming skills and in-depth experience with PyTorch internals.
• Solid understanding of computational graphs and tensor operations.
• Experience building or extending compilers or ML optimization frameworks.

Responsibilities

• Analysis of new models and impacts on compilation stack.
• Develop and maintain frontend compiler infrastructure for PyTorch models.
• Collaborate with other teams throughout feature implementation.

Skills

Python programming

PyTorch internals

Computational graphs understanding

Compiler experience

C++ extensions familiarity

ML model optimization

Education

Degree in Engineering or Computer Science

Tools

LLVM

MLIR

HuggingFace Transformers

Job description

Python / PyTorch Developer — Frontend Inference Compiler – Dubai

UAE

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 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.

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.

As set forth in Cerebras Systems’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.