The Job

AI/Machine Learning Engineer (Embedded Systems, Inference Efficiency)

Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Embedded Systems

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In short

Qualcomm Canada ULC is seeking an AI/Machine Learning Engineer to conduct advanced research in model efficiency, compression, and ML system optimization for on-device inference. This role involves leading research initiatives, collaborating with global teams, and developing systems for future Qualcomm AI accelerators.

Responsibilities

  • Conduct cutting-edge research in inference efficiency and ML system optimization, including efficient architecture design, model compression, PEFT, and compiler stack optimization.
  • Prototype and develop system solutions with software–hardware co-design for optimal model deployment on Qualcomm’s low-power AI accelerators.
  • Collaborate with modeling, compiler, and hardware teams to convert research into production-ready low power AI solutions.
  • Influence future accelerator features and model deployment strategies.
  • Contribute to Qualcomm’s strategic initiatives in efficient AI and embedded intelligence.

Requirements

  • Proven research excellence in inference efficiency and ML systems, 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 algorithms.
  • Strong background in 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 accelerators, including training, fine-tuning, evaluation, and performance optimization.

Desired 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.

Benefits

  • Competitive annual discretionary bonus program.
  • Opportunity for annual RSU grants.
  • Highly competitive benefits package designed to support success at work, at home, and at play.
  • The company offers a competitive annual discretionary bonus program and the opportunity for annual RSU grants.
  • A competitive benefits package is also provided.
#AI#Machine Learning#Embedded Systems#Inference Efficiency#Model Compression#ML System Optimization#Qualcomm
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Company

Qualcomm

Job Posted

1 month ago

Employment Type

Full Time

WorkMode

On Site

Experience Level

Entry

Locations

Markham, Canada

Qualification

Bachelor, Master, Doctoral

Applicants

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