On-Device AI Software Engineer – Remote in Markham

On-Device AI Software Engineer – Remote in Markham

Markham Full-Time 90000 - 110000 $ / year (est.) On-site
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At a Glance

  • Tasks: Develop cutting-edge AI software and optimize code for embedded systems.
  • Company: Join Qualcomm, a leader in tech innovation and AI solutions.
  • Benefits: Competitive salary, health benefits, and opportunities for remote work.
  • Other info: Dynamic team environment with global collaboration and growth potential.
  • Why this job: Make an impact in AI and machine learning while working with advanced technology.
  • Qualifications: Experience in C++17 and a passion for AI and machine learning.

The predicted salary is between 90000 - 110000 $ per year.

Qualcomm Canada ULC in Markham, Ontario, is seeking an Engineer for AI Software/Machine Learning (C++). You will develop a modern C++17 library for Qualcomm Hexagon processors, optimize code for embedded systems, and build model analyzing tools for internal and external customers.

The role involves:

  • Using cross compiler toolchains for Android, embedded Linux, and QNX
  • Addressing issues in existing AI products
  • Implementing ML operations on Hexagon
  • Collaborating with a globally distributed team

On-Device AI Software Engineer – Remote 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.

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Contact Details:

Qualcomm Recruitment Team

We think you need these skills to ace On-Device AI Software Engineer – Remote in Markham

C++17
Embedded Systems Optimization
Machine Learning Operations
Cross Compiler Toolchains
Android Development
Embedded Linux
QNX