AI System/Hardware Architect

Company: Qualcomm Canada ULC

Job Area:

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary:

Do you ever wonder when will connected devices become thinking devices? Be part of the group that is working on technology that will bring “Cognition” to all connected devices: That means devices that don’t just think but instinctively react to their surroundings.

We are searching for a season AI Systems Architecture Engineer to be part of the Qualcomm AI Processor team responsible for analyzing and developing Artificial Intelligence / Machine Learning software applications and use cases developed for Qualcomm Snapdragon processors. The candidate will work on modelling of machine-learning hardware and processors, as well as analysis of new cutting-edge algorithms in the areas of machine learning, computer vision and video processing that bring artificial intelligence to mobile and edge devices.

Responsibilities include analyzing and optimizing custom processors/accelerators, developing and training data-driven architecture models, correlating these models, and performing system-level architecture analysis. Replacement

Qualifications:

• Excellent programming skills in C/C++, Python

• Strong problem-solving skills

• Strong motivation and capabilities in learning new subjects especially in the field of artificial intelligence

• Knowledge of data-driven modelling

• Knowledge of computer and hardware architecture

• Effective interpersonal communications skill (written and verbal)

• Analytical, thorough, resourceful, and detail-oriented

• Self-motivated, hardworking, and flexible

Preferred Qualifications:

• Basic understanding of machine learning, computer vision, and digital image processing algorithms and applications

• Advanced understanding of computer architecture

• Advanced understanding of data-driven modelling

• Excellent verbal, written, and presentation skills

• Ability to work effectively as part of a team

• Knowledge of OOP principles

• Knowledge of GPU Programming / Architecture

Minimum Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 5+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

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