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Job Description:

Developing a deep learning compiler stack that takes neural network descriptions (CNNs/RNNs) created in frameworks such as Caffe, PyTorch, TensorFlow, etc. and converts them into code suitable for execution on special-purpose and embedded platforms.

Use modern compiler frameworks such as LLVM and MLIR.

Developing optimized implementations of a variety of neural-network operations and integrating them into a runtime framework

Developing new optimization techniques and algorithms to efficiently map CNNs onto a wide range of Xtensa processors and specialized hardware.

Benchmarking end-to-end network performance on a variety of DSP and special-purpose accelerator platforms.

Enhancing the framework to improve overall functionality and performance on the various hardware platforms.

Devising multiprocessor/multicore partitioning and scheduling strategies.

Developing complex programs to validate the functionality and performance of the CNN application programming kit.

Working with hardware designers to identify opportunities for additional hardware acceleration of neural network functions.

Working with industry-leading partners and customers to design and standardize neural network APIs..

Nice to have:

Master or PhD. 3+ years of experience working on a production compiler is highly desired. Python experience highly desired Prior work with CNNs and familiarity with deep learning frameworks (TensorFlow, Caffe/2, etc.) is a strong plus Experience programming and optimizing for embedded platforms such as DSPs with DMA engines highly desired Familiarity with the state-of-the-art deep learning compilation approaches (Glow, TVM, XLA, etc.) is a plus Familiarity with various deep learning networks and their applications (Classification/Segmentation/Object Detection/RNNs) is a plus Knowledge of neural net exchange formats (ONNX, NNEF) is a plus

Requirements:

Complete Bachelor in Computer Science or Computer Engineering or equivalent experience. A high level of C and C++ programming expertise with 3-5+ years of experience is required. Expertise in software development on Linux and Windows systems including, test, debug and release is required. Knowledge of and experience with a state-of-the-art compiler stack such as LLVM and MLIR. Experience implementing compilation techniques such loop optimization, polyhedral models, and IR construction/transition/lowering techniques.

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