Job AreaEngineering Group, Engineering Group Machine Learning Engineering General SummaryToday, more intelligence is moving to end devices, and mobile is becoming the pervasive AI platform. Building on the smartphone foundation and the scale of mobile, Qualcomm envisions making AI ubiquitous—expanding beyond mobile and powering other end devices, machines, vehicles, and things. We are inventing, developing, and commercializing power-efficient on-device AI, edge cloud AI, and 5G to make this a reality.

New PositionJob Purpose & ResponsibilitiesAs a member of Qualcomm’s ML Systems Team, you will participate in two activities: Development and evolution of ML/AI compilers (production and exploratory versions) for efficient mappings of ML/AI algorithms on existing and future HW Analysis of ML/AI algorithms and workloads to drive future features in Qualcomm’s ML HW/SW offerings Contributing to the development and evolution of ML/AI compilers within Qualcomm Defining and implementing algorithms for compiling ML/AI workloads to achieve high performance and low power on Qualcomm HW Creating and implementing algorithms that couple PyTorch framework efficiently to Qualcomm ML/AI Compiler flows. Understanding trends in ML network design, through customer engagements and latest academic research, and how this affects both SW and HW design Exploration and analysis of performance/area/power trade-offs for future HW and SW ML algorithms Creation of performance-driven simulation components (using C++, Python) for analysis and design of high-performance HW/SW algorithms on future SoCs Pre-Silicon prediction of performance for various ML algorithms Running, debugging and analyzing performance simulations to suggest enhancements to Qualcomm hardware and software to tackle framework, compute and system memory-related bottlenecks Successful applicants will work in cross-site, cross-functional teams.



Strong background in algorithm development and performance analysis is essential The Following Experiences Would Be Significant Assets Strong knowledge of C++ Strong knowledge of Python Experience in compiler, CPU, DSP and/or GPU design and development is an asset Knowledge of network model formats/platforms (eg.

PyTorch, ONNX) is a solid asset Knowledge of software development processes (revision control, CD/CI, etc.) On-silicon debug skills of high-performance compute algorithms Knowledge of algorithms and data structures Knowledge of computer architecture, digital circuits and event-driven transactional models/simulators Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ 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 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail [email protected] request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. #

📌 Machine Learning Engineer, Frameworks & Performance (New Grad To Principal Level) (Winnipeg)
🏢 Qualcomm
📍 Winnipeg