Intel's Visual Technology Team (VTT) develops best in class compute technology that is a critical part of our major product lines. We are looking for Intern engineers to develop tensor graph compiler targeting machine learning workloads for better utilizing the Gen compute architecture. The machine learning workload team in VTT is responsible for machine learning workload development and performance analysis. We support pre-silicon analysis and projection, Gen architectural technical readiness (TR) support, what-if analysis in TR and beyond.


Responsibilities:
Responsibilities will include, but are not limited to:
• Contribute to the kernel generation to execute tensor graph on Gen architecture
• Develop parameterized machine learning kernels running on Gen architecture
• Maintain and develop code in the regression environment
• Analyze, validate, and report out kernel performance of new Gen compute architecture in pre-Si model

Qualifications

Minimum Qualifications
• Enrolled and working toward PhD Degree in in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
• Programming skills: specifically, python, C++; GPU parallel programming.
• Data analysis, debugging and problem solving skills/experience.
• Experience explaining complex technical concepts.

Preferred Qualifications

An ideal candidate will have knowledge and/or experience in some of the following:
• Deep learning workload understanding, e.g. CNN, RNN etc.
• Machine learning kernel development experience in GPU.
• Understanding compiler and programming language design is a plus
• Tensor compiler experience is a big plus.
• Excellent understanding of GPU compute architecture and technology

Intel Architecture, Graphics, and Software (IAGS) brings Intel's technical strategy to life. We have embraced the new reality of competing at a product and solution level—not just a transistor one. We take pride in reshaping the status quo and thinking exponentially to achieve what's never been done before. We've also built a culture of continuous learning and persistent leadership that provides opportunities to practice until perfection and filter ambitious ideas into execution.