Deep Learning Framework and Compiler Engineer

General Summary:

• Design machine frameworks for Adreno GPU accelerator for computer vision and generative Ai needs
• Good understanding of network architectures, how a deep learning framework optimizes it to efficiently run on target accelerator
• OpenCL (or similar like CUDA) kernel programming knowledge and optimization techniques to get best performance from hardware
• Compiler optimization knowledge at graph level as well tensor IR
• Working experience with any one open source compiler frameworks like TVM, MLIR, LLVM, XLA etc
• Experience of understanding and integrating vendor acceleration SDK like CUDNN, Adreno OpenCLML, TensorRT, ArmNN inot inferenceing frameworks is a plus
• C, C++: Strong programming capability using advanced techniques to design and develop AI compilers and backends.
• Scripting: Strong expertise in Python with design, develop, release and maintain projects.
• AI Frameworks: Familiarity with other AI frameworks like PyTorch, TensorFlow, Hugging Face, etc.Machine Learning Knowledge:
• Understanding of machine learning principles and algorithms starting Computer vision to large language models and continuously update to new trends.Expertise to deep learning accelerator programming (GPU, NPU).
• Any parallel programming experience (Like CUDA, OpenCL, MKLDNN ..etc) is a plus.Experience with deep leaning compilers like Glow, TVM etc is a plus.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience
• ORMaster's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience
• ORPhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience