Edge ML Engineer — Hardware-Driven AI Innovator

Urban Ridge Supplies; Markham; On-site; CAD 114,000 - 164,000; Full time

Job summary

Qualcomm Canada ULC is seeking a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools for efficient discovery and use of state-of-the-art ML solutions across multiple domains. You will collaborate with cross-functional teams to advance ML-enabled hardware and software for mobile, edge, auto, and IoT products.

The role requires experience with ML frameworks, embedded ML development, and leadership capabilities, plus strong communication to senior leadership and

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware/Software/Systems experience.
• Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of hardware/software/systems experience.
• PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of hardware/software/systems experience.

Responsibilities

• Leverages advanced machine learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
• Models, architects, and develops advanced machine learning hardware for inference or training solutions.
• Develops optimized software to enable AI models deployed on hardware and collaborates with hardware teams for joint design and development.
• Develops and applies machine learning techniques into products and AI solutions to enable customers.

Skills

ML frameworks

Embedded systems

Programming (Python/C/C++)

Statistics & probability

Matrixed organization experience

Linux/Android/QNX

Technical leadership

Stakeholder communication

Education

Bachelor's degree

Master's degree

PhD

Job description

Qualcomm Canada ULC is seeking a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools for efficient discovery and use of state-of-the-art ML solutions across multiple domains. You will collaborate with cross-functional teams to advance ML-enabled hardware and software for mobile, edge, auto, and IoT products.

The role requires experience with ML frameworks, embedded ML development, and leadership capabilities, plus strong communication to senior leadership and