Embedded Software Engineer, Machine Learning

Company

the company Canada ULC

Engineering Group >
Machine Learning Engineering

As a member of the Low Power AI solution team, you will play a critical role deploying AI models on the company's low‑power AI accelerator. The position focuses on mapping high‑level machine learning operators to low‑level hardware instructions, involving graph transformation, scheduling, memory planning, individual operator implementation, quantization, and other optimization techniques. Your expertise in machine learning is expected to enhance inference efficiency and accuracy of different models on the company's hardware architecture.

New Position

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• Master’s degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

• Design and implement core components of the ML runtime framework for inference on embedded systems.
• Collaborate with compiler, hardware, and model teams to co‑design efficient execution paths for AI workloads.
• Develop and maintain C/C++ code for runtime kernels and system‑level integration.
• Develop tools to assist with performance profiling and debugging of quantized model accuracy.
• Analyze and improve runtime behaviour using profiling tools and hardware counters.
• Support deployment of models from popular ML frameworks (e.g., Onnx, Tensor Flow, PyTorch) onto the company’s inference stack.

• Strong hands‑on experience in performance optimization for embedded or low‑power systems.
• Proficient in C/C++ programming with a focus on system‑level and runtime development.
• Solid understanding of embedded system design
  , including memory hierarchy and hardware‑software interaction.
• Experience with Linux/Android development environments and tool chains.
• Familiarity with computer architecture
  , especially for AI accelerators or DSPs.
• Basic knowledge of machine learning concepts and model structures.

• Master’s degree in Computer Science, Engineering, or related field.
• 5+ years of experience with ML frameworks (e.g., Tensor Flow, PyTorch, ONNX).
• 5+ years of experience in embedded system development and optimization for ML inference.
• 5+ years of experience with C/C++ in performance‑critical environments.
• Experience with low‑level OS interactions (Linux, Android, QNX).
• Familiarity with quantization, graph optimization, and model deployment pipelines.
• Experience working in cross‑functional teams and large matrixed organizations.

The company is an equal opportunity employer. The company is committed to providing an accessible process for individuals with disabilities and may provide reasonable accommodations upon request.

$ – $

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Salary is only one component of total compensation at the company. The company also offers a competitive annual discretionary bonus program and opportunities for annual RSU grants (employees on sales‑incentive plans are not eligible for the annual bonus).

In addition, the company’s benefits package supports success at work, at home, and at play.