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Senior Embedded Software Engineer (C/C++), Machine Learning

Markham, ON, CA

Pay
$114,400–164,400/yearAnnual period assumed · Location-specific pay — pay source
Pay range and Other Compensation & Benefits: $114,400.00 - $164,400.00 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. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer.
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Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
Apply at Qualcomm

What you’ll work on

Full posting
  • Develop optimized software such as ML kernels, compiler tools and model efficiency tools

  • Extend training or runtime frameworks and model efficiency tools with new features

  • Develop, adapt, or prototype complex ML algorithms, models, or frameworks

  • Run complex experiments to train and evaluate ML models and software

  • Help model and architect ML hardware co-designed with ML software

From the employer’s posting
Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.)
Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
Develops, adapts, or prototypes complex machine learning algorithms, models, or frameworks
Conducts complex experiments to train and evaluate machine learning models and/or software independently.
Models, architects, and develops machine learning hardware (co-designed with machine learning software)

What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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. OR 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. OR PhD in Computer Science, Engineering, Information Systems, or related field.
Education & alternatives
Minimum Qualifications: • 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. OR 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. OR PhD in Computer Science, Engineering, Information Systems, or related field. Preferred Qualifications:
Preferred Qualifications: * Master's degree in Computer Science, Engineering, Information Systems, or related field. * 2+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras). * 2+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media). * 2+ years of experience with C/C++, ideally at the embedded level * 2+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule). * 2+ years experience working in a large matrixed organization. * 1+ year of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware. * 1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above). Principal Duties and Responsibilities:

Tools in this posting

  • C
  • C++
  • Keras
  • PyTorch
Source — Tool mentions in context
Skills / Experience Required: * Solid hands-on skills and experience on performance optimization. * Proficient programming skills in C/C++ * Machine learning knowledge is a plus.. * Experience with Linux/Android development environment and tools. * Familiar with embedded/computer hardware architecture. Minimum Qualifications:
Preferred Qualifications: * Master's degree in Computer Science, Engineering, Information Systems, or related field. * 2+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras). * 2+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media). * 2+ years of experience with C/C++, ideally at the embedded level * 2+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule). * 2+ years experience working in a large matrixed organization. * 1+ year of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware. * 1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above). Principal Duties and Responsibilities:

Posting record

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Status in our records
Live
First seen by us
Aug 15, 2026 · 76 days ago
Recorded sightings
146
Last seen by us
Oct 30, 2026

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Job description

View original posting ↗

## Company: Qualcomm Canada ULC ## Job Area: Engineering Group, Engineering Group > Machine Learning Engineering General Summary: As a member of Low Power AI solution team, you will play a critical role at deploying AI models on Qualcomm's low power AI accelerator. The position focuses on mapping high level machine learning operators to low level hardware instructions, involving various optimization techniques: graph transformation, scheduling, memory planning, individual operator implementation, quantization, etc. Your expertise at machine learning is expected to enhance inference efficiency and accuracy of different models on Qualcomm's hardware architecture. New Position Skills / Experience Required: * Solid hands-on skills and experience on performance optimization. * Proficient programming skills in C/C++ * Machine learning knowledge is a plus.. * Experience with Linux/Android development environment and tools. * Familiar with embedded/computer hardware architecture. Minimum Qualifications: • 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. OR 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. OR PhD in Computer Science, Engineering, Information Systems, or related field. Preferred Qualifications: * Master's degree in Computer Science, Engineering, Information Systems, or related field. * 2+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras). * 2+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media). * 2+ years of experience with C/C++, ideally at the embedded level * 2+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule). * 2+ years experience working in a large matrixed organization. * 1+ year of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware. * 1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above). Principal Duties and Responsibilities: * Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations. * Models, architects, and develops machine learning hardware (co-designed with machine learning software) for inference or training solutions. * Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development. * Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same. * Develops, adapts, or prototypes complex machine learning algorithms, models, or frameworks aligned with and motivated by product proposals or roadmaps with minimal guidance from more experienced engineers. * Conducts complex experiments to train and evaluate machine learning models and/or software independently. 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. Pay range and Other Compensation & Benefits: $114,400.00 - $164,400.00 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. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer. If you would like more information about this role, please contact Qualcomm Careers.
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Pay
Pay range and Other Compensation & Benefits: $114,400.00 - $164,400.00 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. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer.
Location & working pattern

Markham, ON, CA

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