Deep learning framework and compiler Engineer

Company: Qualcomm India Private LimitedJob Area: Engineering Group, Engineering Group > Systems EngineeringGeneral 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.Deep learning framework and compiler Engineer 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. experience. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail or call Qualcomm's toll-free number found . 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