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Machine Learning Engineer, Frameworks & Performance (New Grad to Principal level)

Markham, ON, CA

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What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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. OR 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. OR PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Tools in this posting

  • Python
  • Docker
  • PyTorch
  • C++
Source — Tool mentions in context
Key Responsibilities: * 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.
The following experiences would be significant assets: * Strong object-oriented design principles * 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 strong asset * Knowledge of software development processes (revision control, CD/CI, etc.) * Familiarity with tools such as git, Jenkins, Docker, clang/MSVC * 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 Minimum Qualifications:

Job description

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## Company: Qualcomm Canada ULC ## Job Area: Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Today, 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 Position Job Purpose & Responsibilities: As 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 Key Responsibilities: * 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. Requirements: * Demonstrated ability to learn, think and adapt in fast changing environment * Detail-oriented with strong problem-solving, analytical and debugging skills * Strong communication skills (written and verbal) * Strong background in algorithm development and performance analysis is essential The following experiences would be significant assets: * Strong object-oriented design principles * 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 strong asset * Knowledge of software development processes (revision control, CD/CI, etc.) * Familiarity with tools such as git, Jenkins, Docker, clang/MSVC * 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 Minimum Qualifications: • 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. OR 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. OR PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. Applicants: Qualcomm is an equal opportunity employer. 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 disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon 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. We will not respond here to requests for updates on applications or resume inquiries). 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. To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

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Markham, ON, CA

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First seen by us
Aug 27, 2026
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Last seen by us
Oct 10, 2026

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