ML/AI Compiler Engineer: Frameworks & Performance in Markham

ML/AI Compiler Engineer: Frameworks & Performance in Markham

Markham Full-Time 135000 - 165000 $ / year (est.) On-site
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At a Glance

  • Tasks: Develop and optimize ML/AI compilers for Qualcomm hardware, focusing on performance and power efficiency.
  • Company: Join Qualcomm Canada, a leader in advancing on-device AI technology.
  • Benefits: Enjoy competitive salary, health benefits, and opportunities for remote work.
  • Other info: Collaborative environment with great potential for career growth.
  • Why this job: Make a real impact in AI by working on cutting-edge compiler technologies.
  • Qualifications: Strong background in algorithms, C++/Python programming, and ML frameworks required.

The predicted salary is between 135000 - 165000 $ per year.

Qualcomm Canada ULC is advancing on-device AI by developing ML/AI compilers for efficient mapping of workloads on Qualcomm hardware.

You will contribute to compiler development, optimize performance and power, and study ML workloads to inform future HW/SW features, with a focus on Py Torch integration and cross-functional collaboration.

The role requires a strong background in algorithms, performance analysis, and programming in C++/Python, with experience in ML frameworks and compiler flows.

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ML/AI Compiler Engineer: Frameworks & Performance in Markham employer: QUALCOMM, Inc.

Qualcomm Canada ULC is an exceptional employer that fosters a dynamic work culture focused on innovation and collaboration in the field of AI and machine learning. Located in a vibrant tech hub, employees benefit from competitive compensation, a comprehensive benefits package, and ample opportunities for professional growth and development. Join a team that not only values your contributions but also supports your journey in shaping the future of connected devices.

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Contact Details:

QUALCOMM, Inc. Recruitment Team

We think you need these skills to ace ML/AI Compiler Engineer: Frameworks & Performance in Markham

Compiler Development
Performance Optimization
Power Optimization
Machine Learning Workloads Analysis
PyTorch Integration
Cross-Functional Collaboration
Algorithms