Deep Learning Libraries engineer

Rivos is developing optimized Deep Learning operators for its SIMT (Single Instruction Multiple Threads) machine, providing optimal use of the compute units the HW exposes. You will contribute to development and optimization of many operators used for both training and inference of Deep Neural Networks. In this process you will be able to influence the architectural decision of the HW engine to deliver more performant and more power efficient solutions. In a vertical development approach you will be contributing extensively to all the other parts of the solution : client software, compiler, runtime, simulator to help define the next generations of our solution.

Responsibilities

As a Deep Learning Libraries engineer, you will own or participate in the following

design and implement critical parts of the DL operators libraries, including kernels used by PyTorch

contribute to the performance analysis flow to guide optimization work

contribute to the functional and performance ISA simulators

collaborate cross-functionally with Silicon design, architecture experts, and other teams across the company

Requirements

at least 3 years of experience in software library development (C, C++)

strong C++ programming skills

strong knowledge of parallel programming languages

strong background in computer architecture and deep learning

experience with PyTorch a plus

excellent skills in problem solving, written and verbal communication, excellent organization skills, and highly self-motivated.

ability to work well in a team and be productive under aggressive schedules

Education and Experience

PhD, Master's Degree or Bachelor's Degree in technical subject area.

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