Neural Rendering Researcher in Markham at honor foundations

Date Posted: 4/4/2025

Job Snapshot

  • Employee Type:
    Full-Time
  • Location:
    Markham
  • Job Type:
  • Experience:
    Not Specified
  • Date Posted:
    4/4/2025

Job Description


Company:

Qualcomm Canada ULC

Job Area:

Engineering Group, Engineering Group > Machine Learning Researcher

General Summary:

Qualcomm AI Research is looking for world-class researchers in deep learning, to join a high-caliber team of engineers inventing machine learning technology to provide best-in-class solutions while running with the most efficient use of power, memory, and computation.

Members of our team are part of a multi-disciplinary core research group within Qualcomm which spans software, hardware, and systems, and our members may simultaneously contribute to technology deployed worldwide by partnering with our industry-leading businesses across mobile, compute, automotive, cloud, and IOT. Our research team has demonstrated first-in-the-world research and proof-of-concepts in areas such model efficiency, neural video codecs, video semantic segmentation, federated learning, and wireless RF sensing (https://www.qualcomm.com/ai-research), has won major research competitions such as the visual wake word challenge, and converted leading research into best-in-class user-friendly tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet).

Minimum Qualifications:

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field.

• 6+ months of experience developing and/or optimizing machine learning models, systems, platforms, or methods.

The R&D work responsibility for this position focuses on the following 

  • Deep learning research on real-time rendering and neural reconstruction (e.g. neural radiance fields, super-resolution for gaming, neural denoising of ray-traced images…)

  • Identify, study, and reproduce the state-of-the-art

  • Innovate, create demos, and publish at top-tier conferences


Ideal candidates will demonstrate the following: 

  • ​Master’s degree in Computer Science, Engineering, Information Systems, or related field.  

  • Solid foundation in deep learning

  • Extensive experience in modeling, implementing, and training neural networks in high-level languages and frameworks like PyTorch or TensorFlow 


Other desirable skills: 

  • Ability to drive early-stage research

  • Experience with NeRFs or similar models

  • Experience with super-resolution models

  • Track record of research excellence and high-quality publications (e.g. SIGGRAPH, ICLR, NeurIPS, CVPR, ICML, ICCV, etc.)  

  • PhD in Computer Science, Engineering, or related field 
     

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.

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If you would like more information about this role, please contact Qualcomm Careers.

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