Senior Embedded ML Engineer — Low-Power On-Device AI

Qualcomm; Markham; On-site; CAD 157,000 - 226,000; Full time

Job summary

A leading technology company in Canada is looking for a Machine Learning Engineer to work on low-power AI solutions. The role involves deploying AI models and optimizing machine learning architectures for efficiency. Candidates must have experience in machine learning research, with a strong track record in inference efficiency and proficiency in Python and C/C++. A Bachelor's degree in a related field is required, along with the ability to work within strict computational constraints. Competitive compensation and benefits are provided.

Benefits

Competitive annual discretionary bonus

Annual RSU grants

Comprehensive benefits package

Qualifications

• Strong track record in machine learning research or advanced applied ML development.
• Deep understanding of ML model architecture and performance characteristics.
• Hands-on experience with quantization and reduced-precision inference.
• Ability to prototype and analyze ideas under strict constraints.
• Proficiency in Python and C/C++, comfortable with low-level execution.

Responsibilities

• Explore novel ML model architectures for low-power inference.
• Align architectural choices and dataflows with Qualcomm's hardware.
• Design and evaluate quantization and compression techniques.
• Develop and optimize computational graphs and memory-aware execution.
• Conduct performance investigations using profiling tools.

Skills

Machine learning research

Inference efficiency

Python

C/C++

Computer architecture

Hardware-aware optimization

Education

Bachelor's degree in Computer Science, Engineering, Information Systems or related field

Master's degree in Computer Science, Engineering, Information Systems or related field

PhD in Computer Science, Engineering, Information Systems or related field

Job description

A leading technology company in Canada is looking for a Machine Learning Engineer to work on low-power AI solutions. The role involves deploying AI models and optimizing machine learning architectures for efficiency. Candidates must have experience in machine learning research, with a strong track record in inference efficiency and proficiency in Python and C/C++. A Bachelor's degree in a related field is required, along with the ability to work within strict computational constraints. Competitive compensation and benefits are provided.