Sr Embedded Machine Learning Engineer

Qualcomm • Markham, ON

34d

About The Position

We are seeking a Machine Learning software engineer with embedded experience.
Qualcomm Automotive AI Software team is rapidly expanding to offer optimized solutions for infotainment and ADAS/Autonomous Driving. To scale and strengthen our offering in this domain, we are looking for a talented engineer to develop and deliver novel embedded AI solutions to enable state-of-the-art AI models on auto platforms for millions of end users. Replacement.

Requirements

• Strong hands-on experience in performance optimization for embedded or low-power systems.
• Excellent in 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/QNX development environments and toolchains.
• Familiarity with computer architecture, especially for AI accelerators or DSPs.
• Solid knowledge of machine learning concepts and model structures.
• Optimization of algebraic operations in algorithms for HW cores.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ 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 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• PhD in Computer Science, Engineering, Information Systems, or related field.

Nice To Haves

• Knowledge on deep learning and popular frameworks is an asset.

Responsibilities

• 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++ 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 behavior using profiling tools and hardware counters.
• Support deployment of models from popular ML frameworks (e.g., Onnx, TensorFlow, PyTorch) onto Qualcomm’s inference stack.
• Challenging the status quo and driving innovations to be the best-of-class.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree