Embedded ML Engineer — C/C++, Low-Power AI

QUALCOMM, Inc.; Markham; On-site; CAD 105,000 - 155,000; Full time

Benefits offered by this job

Competitive benefits

Discretionary annual bonus program

RSU grants

Job summary

Qualcomm Canada ULC is seeking a machine learning engineer focused on mapping high-level operators to low-level hardware instructions for a low-power AI accelerator. You will optimize graphs, scheduling, memory planning and operator implementations to improve inference efficiency on Qualcomm hardware.

The role requires strong C/C++ skills, Linux/Android experience, and knowledge of embedded systems. Experience with major ML frameworks and a Master's degree are preferred.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
• Master's degree in CS/engineering or related field preferred.
• 2+ years experience with ML frameworks (TensorFlow, Caffe, PyTorch, Keras).
• 2+ years embedded system development and optimization for ML.

Responsibilities

• Applies ML knowledge to extend training or runtime frameworks and optimize software tools.
• Architects and develops ML hardware co-designed with ML software for inference/training.
• Develops optimized software to enable AI models on Qualcomm hardware (kernels, compilers).
• Prototypes ML algorithms and conducts experiments to evaluate models.

Skills

Performance optimization

C/C++

Machine learning

Linux/Android development

Embedded hardware

Education

Bachelor's degree in Computer Science/Engineering/IS

Master's degree (preferred)

Tools

TensorFlow

Caffe

Caffe2

PyTorch

Keras

Job description

Qualcomm Canada ULC is seeking a machine learning engineer focused on mapping high-level operators to low-level hardware instructions for a low-power AI accelerator. You will optimize graphs, scheduling, memory planning and operator implementations to improve inference efficiency on Qualcomm hardware.

The role requires strong C/C++ skills, Linux/Android experience, and knowledge of embedded systems. Experience with major ML frameworks and a Master's degree are preferred.