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 âCognitionâ to all connected devices: That means devices that donât 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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