Job Description: You will be part of RD pathfinding team working on co-design of distributed system to enable parallel high-performance machine learning applications. You will work closely with strategic machine learning partners to analyze their applications, identify system level performance bottlenecks, and formulate architectural recommendations to the Intel architecture team that will help increase the system level performance, scalability and energy efficiency of these applications. In addition, you will also collaborate with machine learning partners to suggest algorithmic and architectural optimization opportunities in their codes to benefit from various features on Intel future platforms. Ability and desire to deeply understand application needs and algorithms, and rethink the algorithms to achieve high efficiency on a various hardware architectures, including distributed systems. Strong mathematical background (eg., mathematical optimization, statistics, applied numerical linear algebra, etc.), and experience with the state-of-the-art machine learning techniques, such as deep neural networks. Extensive hands-on experience with one of the deep learning framework, such as Caffe, TensorFlow, or Theano and a good working knowledge of C/C++.
You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.Experience listed below would be obtained through a combination of your school work/classes/research and/or relevant previous job and/or internship experiences. Minimum Qualifications: – Background in hardware architecture (pipelining, memory hierarchies, DRAM characteristics, power and area estimates, etc.) – Experience developing optimized and parallelized machine learning kernels or applications for at least one hardware target, such as multicore Intel CPUs/SSE/AVX, GPUs, or custom accelerators. – Ph.D., or experience in a research environment such as a national lab, or 4+ years industry experience.
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