At a Glance
- Tasks: Conduct cutting-edge research on AI model efficiency and collaborate on innovative solutions.
- Company: Join Qualcomm, a leader in tech innovation with a focus on AI and embedded systems.
- Benefits: Competitive salary, bonuses, RSU grants, and a comprehensive benefits package.
- Other info: Opportunities for career growth and a commitment to accessibility for all applicants.
- Why this job: Shape the future of AI technology while working with global teams on impactful projects.
- Qualifications: Bachelor's degree in relevant field and experience in ML system optimization required.
The predicted salary is between 40000 - 164400 $ per year.
As a member of the Low Power AI Solution team, you will conduct advanced research on model efficiency, model compression techniques, and ML system optimization to push the boundaries of efficient on-device inference. You will lead and contribute to high-impact research initiatives, understand hardware–software interactions at a fundamental level, and collaborate with global teams to develop systems that shape future Qualcomm AI accelerator capabilities.
Key Responsibilities
- Conduct cutting-edge research in inference efficiency and ML system optimization: efficient architecture design, model compression, PEFT, compiler stack optimization etc.
- Prototype and develop system solutions with software–hardware co-design to align architectural choices, dataflows, and memory behavior with Qualcomm’s low-power AI accelerators for optimal model deployment.
- Collaborate closely with modeling, compiler, and hardware teams to convert research into production-ready low power AI solutions, enabling real-world applications and commercial impact.
- Influence future accelerator features and model deployment and contribute to Qualcomm’s strategic initiatives in efficient AI and embedded intelligence.
Requirements
- Proven research excellence on inference efficiency and ML system, demonstrated by publications, community contributions, or equivalent evidence of impact.
- Deep expertise in neural network architectures, model compression (e.g., quantization, pruning, knowledge distillation) and efficient inference algorithm.
- Strong background on compiler stack and ML system optimization for AI accelerators (e.g., graph transformation, graph tiling and scheduling, tensor layout/memory optimization).
- Strong understanding of Machine Learning fundamentals, strong programming skills with ML frameworks.
- Hands-on experience with model development pipelines for AI accelerator, including training, fine-tuning, evaluation, and performance optimization.
Preferred Qualifications
- PhD in Computer Science, Electrical Engineering, or related fields or MS with AI research, or related work experience.
- Extensive experience in deep learning research and impactful publications in top-tier machine learning venues (NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, EMNLP etc.).
- Experience in on-device model deployment and optimization algorithms for AI hardware accelerators.
- Experience working with a variety of stakeholders and ability to communicate complex outcomes to a wide range of audiences.
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.
- 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.
AI/Machine Learning Engineer in Markham employer: Qualcomm
Qualcomm Canada ULC is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for Display Silicon System Debug Engineers to thrive. With a strong emphasis on employee growth, you will have access to mentorship opportunities and the chance to work alongside industry leaders in a cutting-edge environment. Located in Canada, the company offers competitive benefits and a commitment to work-life balance, ensuring that you can pursue meaningful and rewarding employment while contributing to groundbreaking technology.
