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Researcher – Computer Vision and Multimodal Foundation Models

    • Markham, Ontario
  • 69t61

Job description

Huawei Canada has an immediate permanent opening for a Researcher.

About the team:

Founded in 2012, the Noah’s Ark lab has evolved into a prominent research organization with notable achievements in academia and industry. The lab’s mission focuses on advancing artificial intelligence and related fields to benefit the company and society. Driven by impactful, long-term projects, the aim is to enhance state-of-the-art research while integrating innovations into the company's products and services, including LLMs, RL, NLP, computer vision, AI theory, and Autonomous driving.

Responsibilities:

  • Independently contribute to research and development efforts within the area of computer vision and multimodal foundation models.

  • Collaborate closely with cross-functional teams to integrate computer vision solutions into the broader spatial reasoning system.

  • Mentor and guide junior engineers and interns, fostering a collaborative and innovative team environment.

  • Contribute to the development of our intellectual property portfolio through patent filings and publications.

  • Stay abreast of the latest research and advancements in computer vision and machine learning. Proactively identify opportunities for innovation.

  • Independently manage projects and deliver high-quality results within established timelines.

Job requirements

  • Advanced degree (Ph.D. preferred) in Computer Science, Robotics, or a related field with a focus on computer vision and multimodal foundation models.

  • Deep understanding of spatial reasoning and foundation models, e.g., VLM, LLM, MLLM, etc.

  • Proven expertise in applying computer vision algorithms for real-world application.

  • Strong programming skills in Python and C++, with experience using deep learning frameworks (PyTorch, TensorFlow).

  • Excellent problem-solving and analytical skills, with the ability to tackle complex technical challenges.

  • A strong publication record in top-tier AI conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, AAAI, etc.).

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