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.

• 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

• at least 3 years of experience numerical library development
• strong C++ programming skills
• strong knowledge of parallel programming languages
• experience with PyTorch a plus
• strong background in dense linear algebra software
• 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.