Software Engineer, Compiler (Front-end)

Responsibilities

• Design and implement the front-end pipeline that transforms models from major deep learning frameworks such as PyTorch into the compiler's internal IR
• Develop graph-level optimizations, including operator fusion, constant folding, shape inference, and layout transformations
• Build extensible model ingestion structures for architectures such as LLM, VLA, and Multimodal models
• Design and evolve a tensor-level kernel language that exposes the capabilities of the internal IR and DSL
• Establish verification mechanisms to ensure correctness throughout the translation process
• Collaborate with software teams and language users to refine language design

Requirements

• Bachelor's degree in Computer Science, Mathematics, or a related field
• Experience or familiarity with compilers or program transformation systems
• Understanding of deep learning frameworks like PyTorch, TensorFlow, and ONNX
• Proficiency in Python
• Experience with a systems programming language such as Rust or C++

Preferred Qualifications

• Master's or PhD in Programming Languages, Compilers, or Program Analysis
• Experience designing domain-specific languages (DSLs)
• Deep understanding of PyTorch compiler internals (TorchDynamo, FX Graph, torch.compile)
• Experience with compiler frameworks such as LLVM, MLIR, or TVM
• Understanding of AI accelerator architectures (NPU, GPU, TPU)
• Experience with graph-level compilation optimizations