Engineer, AI Framework Software (Compiler Developer)

Responsibilities:

• Develop and optimize compiler toolchains for ML accelerators, including front-end parsing, intermediate representation (IR) transformations, and backend code generation.
• Implement and enhance ML-specific optimizations such as operator fusion, memory layout transformations, quantization-aware compilation, and scheduling.
• Collaborate with hardware architects to co-design compiler optimizations aligned with accelerator capabilities.
• Work on ML frameworks (PyTorch, ONNX) to integrate compiler passes for efficient execution on target hardware.
• Improve performance through domain-specific optimizations, autotuning, and parallelization techniques.
• Debug and analyze performance bottlenecks across software and hardware stacks.
• Develop automated testing, benchmarking, and profiling tools for validating compiler optimizations.

Qualifications:

• Strong proficiency in compiler development, including experience with LLVM, MLIR, TVM, or similar frameworks.
• Expertise in Machine Learning model execution, optimization, and deployment.
• Strong programming skills in C++, Python, and assembly-level optimizations.
• Knowledge of parallel computing, vectorization, and memory hierarchy optimizations.
• Familiarity with deep learning frameworks (TensorFlow, PyTorch, ONNX).
• Strong analytical skills for performance profiling and debugging.
• Experience in graph optimizations, quantization, and code generation.

Preferred Qualifications

• Knowledge of heterogeneous computing, DSPs, and low-level hardware programming.
• Familiarity with AI model deployment and inference optimization techniques.
• Background in high-performance computing (HPC).